Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: Vitamins and Minerals Help Fight Coronavirus

Abstract:
Optimal nutrition can improve well-being and might mitigate the risk and morbidity associated with coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).
This review summarizes nutritional guidelines to support dietary counseling provided by dietitians and health-related professionals.
The majority of documents encouraged the consumption of fruits, vegetables, and whole grain foods.
Thirty-one percent of the guidelines highlighted the importance of minerals and vitamins such as zinc and vitamins C, A, and D to maintain a well-functioning immune system.
Dietary supplementation has not been linked to COVID-19 prevention.
However, supplementation with vitamins C and D, as well as with zinc and selenium, was highlighted as potentially beneficial for individuals with, or at risk of, respiratory viral infections or for those in whom nutrient deficiency is detected.
There was no convincing evidence that food or food packaging is associated with the transmission of COVID-19, but good hygiene practices for handling and preparing foods were recommended.
No changes to breastfeeding recommendations have been made, even in women diagnosed with COVID-19.

Answer: {"verdict": "CONTRADICT", "evidence": ["The majority of documents encouraged the consumption of fruits, vegetables, and whole grain foods.", "Thirty-one percent of the guidelines highlighted the importance of minerals and vitamins such as zinc and vitamins C, A, and D to maintain a well-functioning immune system.", "Dietary supplementation has not been linked to COVID-19 prevention.", "However, supplementation with vitamins C and D, as well as with zinc and selenium, was highlighted as potentially beneficial for individuals with, or at risk of, respiratory viral infections or for those in whom nutrient deficiency is detected."]}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: Masks do reduce spread of flu and some COVID-19

Abstract:
Evidence that face masks provide effective protection against respiratory infections in the community is scarce.
However, face masks are widely used by health workers as part of droplet precautions when caring for patients with respiratory infections.
It would therefore be reasonable to suggest that consistent widespread use of face masks in the community could prevent further spread of the Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2).
In this study we examine public face mask wearing in Uganda where a proportion wears masks to protect against acquiring, and the other to prevent from transmitting SARS-CoV-2.
The objective of this study was to determine what percentage of the population would have to wear face masks to reduce susceptibility to and infectivity of COVID-19 in Uganda, keeping the basic reproduction number below unity and/or flattening the curve.
We used an SEIAQRD model for the analysis.
Results show that implementation of facemasks has a relatively large impact on the size of the coronavirus epidemic in Uganda.
We find that the critical mask adherence is 5 per 100 when 80% wear face masks.
A cost-effective analysis shows that utilizing funds to provide 1 public mask to the population has a per capita compounded cost of USD 1.34.
If provision of face masks is done simultaneously with supportive care, the per capita compounded cost is USD 1.965, while for the case of only treatment and no provision of face masks costs each Ugandan USD 4.0579.
We conclude that since it is hard to achieve a 100% adherence to face masks, government might consider provision of face masks in conjunction with provision of care.

Answer: {"verdict": "SUPPORT", "evidence": ["It would therefore be reasonable to suggest that consistent widespread use of face masks in the community could prevent further spread of the Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2)."]}


Question:
You will be shown a claim related to the COVID-19 pandemic, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT".
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract.

For instance, if the model were given the claim "the COVID vaccine is safe for healthy adults", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that the risks of severe COVID vaccine side effects are low for healthy adults."]
}

Claim: Chadox1 ncov-19 vaccination prevents sars-cov-2 pneumonia in rhesus macaques

Abstract:
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) emerged in December 20191,2 and is responsible for the COVID-19 pandemic3.
Vaccines are an essential countermeasure urgently needed to control the pandemic4.
Here, we show that the adenovirus-vectored vaccine ChAdOx1 nCoV-19, encoding the spike protein of SARS-CoV-2, is immunogenic in mice, eliciting a robust humoral and cell-mediated response.
This response was not Th2 dominated, as demonstrated by IgG subclass and cytokine expression profiling.
A single vaccination with ChAdOx1 nCoV-19 induced a humoral and cellular immune response in rhesus macaques.
We observed a significantly reduced viral load in bronchoalveolar lavage fluid and respiratory tract tissue of vaccinated animals challenged with SARS-CoV-2 compared with control animals, and no pneumonia was observed in vaccinated rhesus macaques.
Importantly, no evidence of immune-enhanced disease following viral challenge in vaccinated animals was observed.
ChAdOx1 nCoV-19 is currently under investigation in a phase I clinical trial.
Safety, immunogenicity and efficacy against symptomatic PCR-positive COVID-19 disease will now be assessed in randomised controlled human clinical trials.

Answer: {"verdict": "SUPPORT", "evidence": ["A single vaccination with ChAdOx1 nCoV-19 induced a humoral and cellular immune response in rhesus macaques.", "We observed a significantly reduced viral load in bronchoalveolar lavage fluid and respiratory tract tissue of vaccinated animals challenged with SARS-CoV-2 compared with control animals, and no pneumonia was observed in vaccinated rhesus macaques."]}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: Wear masks with two or more layers to stop the spread of COVID-19

Abstract:
The COVID‐19 pandemic caused by the novel coronavirus SARS‐CoV‐2 has claimed many lives worldwide.
Wearing medical masks or N95 masks (namely N95 respirators) can slow the virus spread and reduce the infection risk.
Reuse of these masks can minimize waste, protect the environment, and help to solve the current imminent shortage of masks.
Disinfection of used masks is needed for reuse of them with safety, but improper decontamination can damage the blocking structure of masks.
In this study, we demonstrated, using avian coronavirus of infectious bronchitis virus to mimic SARS‐CoV‐2, that medical masks and N95 masks remained their blocking efficacy after being steamed on boiling water even for 2 hours.
We also demonstrated that three brands of medical masks blocked over 99% viruses in aerosols.
The avian coronavirus was completely inactivated after being steamed for 5 minutes.
Together, this study suggested that medical masks are adequate for use on most social occasions, and both medical masks and N95 masks can be reused for a few days with steam decontamination between use.
This article is protected by copyright.
All rights reserved.

Answer: {"verdict": "SUPPORT", "evidence": ["Wearing medical masks or N95 masks (namely N95 respirators) can slow the virus spread and reduce the infection risk.", "We also demonstrated that three brands of medical masks blocked over 99% viruses in aerosols.", "The avian coronavirus was completely inactivated after being steamed for 5 minutes.", "Together, this study suggested that medical masks are adequate for use on most social occasions, and both medical masks and N95 masks can be reused for a few days with steam decontamination between use."]}


Question:
You will be shown a claim related to the COVID-19 pandemic, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT".
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract.

For instance, if the model were given the claim "the COVID vaccine is safe for healthy adults", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that the risks of severe COVID vaccine side effects are low for healthy adults."]
}

Claim: Blood-based culture of sars-cov-2 informs infectivity and safe de-isolation assessments during covid-19

Abstract:
BACKGROUND: The detection of SARS-CoV-2 RNA by real-time polymerase chain reaction (PCR) in respiratory samples collected from persons recovered from COVID-19 does not necessarily indicate shedding of infective virions.
By contrast, the isolation of SARS-CoV-2 using cell-based culture likely indicates infectivity, but there are limited data on the correlation between SARS-CoV-2 culture and PCR.
METHODS: One hundred and ninety-five patients with varying severity of COVID-19 were tested (outpatients [n=178]), inpatients [n=12] and critically unwell patients admitted to the intensive care unit [ICU; n=5]).
SARS-CoV-2 PCR positive samples were cultured in Vero C1008 cells and inspected daily for cytopathic effect (CPE).
SARS-CoV-2-induced CPE was confirmed by PCR of culture supernatant.
Where no CPE was observed, PCR was performed on day four to confirm absence of virus replication.
Cycle threshold (Ct) of the day four PCR (Ctculture) and the PCR of the original clinical sample (Ctsample) were compared, and positive cultures were defined where Ctsample-Ctculture was ≥3.
FINDINGS: Of 234 samples collected, 228 (97%) were from the upper respiratory tract.
SARS-CoV-2 was only successfully isolated from samples with Ctsample ≤32, including in 28/181 (15%), 19/42 (45%) and 9/11 samples (82%) collected from outpatients, inpatients, and ICU patients, respectively.
The mean duration from symptom onset to culture positivity was 4.5 days (range 0-18).
SARS-CoV-2 was significantly more likely to be isolated from samples collected from inpatients (p<0â001) and ICU patients (p<0â0001) compared with outpatients respectively, and in samples with lower Ctsample.
CONCLUSION: SARS-CoV-2 culture may be used as a surrogate marker for infectivity and inform de-isolation protocols.

Answer: {"verdict": "CONTRADICT", "evidence": ["By contrast, the isolation of SARS-CoV-2 using cell-based culture likely indicates infectivity, but there are limited data on the correlation between SARS-CoV-2 culture and PCR."]}


Question:
You will be shown a claim related to the COVID-19 pandemic, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT".
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract.

For instance, if the model were given the claim "the COVID vaccine is safe for healthy adults", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that the risks of severe COVID vaccine side effects are low for healthy adults."]
}

Claim: Berberine and obatoclax are sars-cov-2 replication in primary human nasal epithelial cells in vitro.

Abstract:
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged as a new human pathogen in late 2019 and has infected an estimated 10% of the global population in less than a year.
There is a clear need for effective antiviral drugs to complement current preventive measures including vaccines.
In this study, we demonstrate that berberine and obatoclax, two broad-spectrum antiviral compounds, are effective against multiple isolates of SARS-CoV-2.
Berberine, a plant-derived alkaloid, inhibited SARS-CoV-2 at low micromolar concentrations and obatoclax, originally developed as an anti-apoptotic protein antagonist, was effective at sub-micromolar concentrations.
Time-of-addition studies indicated that berberine acts on the late stage of the viral life cycle.
In agreement, berberine mildly affected viral RNA synthesis, but strongly reduced infectious viral titers, leading to an increase in the particle-to-pfu ratio.
In contrast, obatoclax acted at the early stage of the infection, in line with its activity to neutralize the acidic environment in endosomes.
We assessed infection of primary human nasal epithelial cells cultured on an air-liquid interface and found that SARS-CoV-2 infection induced and repressed expression of a specific set of cytokines and chemokines.
Moreover, both obatoclax and berberine inhibited SARS-CoV-2 replication in these primary target cells.
We propose berberine and obatoclax as potential antiviral drugs against SARS-CoV-2 that could be considered for further efficacy testing.

Answer: {"verdict": "CONTRADICT", "evidence": ["In this study, we demonstrate that berberine and obatoclax, two broad-spectrum antiviral compounds, are effective against multiple isolates of SARS-CoV-2.", "Berberine, a plant-derived alkaloid, inhibited SARS-CoV-2 at low micromolar concentrations and obatoclax, originally developed as an anti-apoptotic protein antagonist, was effective at sub-micromolar concentrations.", "Moreover, both obatoclax and berberine inhibited SARS-CoV-2 replication in these primary target cells."]}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: People with diabetes have not a higher risk for complications from coronavirus

Abstract:
Some comorbidities are associated with severe coronavirus disease (Covid-19) but it is unclear whether some increase susceptibility to Covid-19.
In this case-control Mexican study we found that obesity represents the strongest predictor for Covid-19 followed by diabetes and hypertension in both sexes and chronic renal failure in females only.
Active smoking was associated with decreased odds of Covid-19.
These findings indicate that these comorbidities are not only associated with severity of disease but also predispose for getting Covid-19.
Future research is needed to establish the mechanisms involved in each comorbidity and the apparent "protective" effect of cigarette smoking.

Answer: {"verdict": "CONTRADICT", "evidence": ["In this case-control Mexican study we found that obesity represents the strongest predictor for Covid-19 followed by diabetes and hypertension in both sexes and chronic renal failure in females only."]}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: it's also important to have a strong immune system that can fight back against the germs you may encounter.

Abstract:
This review evaluates whether pregnancy is a risk factor for COVID-19 by looking at the expression of immune markers such as immune cells and cytokines in order to have a better understanding on the pathophysiology of the disease, thus reducing maternal deaths.
Pregnant women are more at risk of contracting COVID-19 due to their weakened immune system.
Studies demonstrate that COVID-19 is an immune condition which is marked by reduced lymphocytes and elevated selected proinflammatory cytokines.
Similar immune expression has been demonstrated in pregnancy by several studies.
In addition, the placenta has been shown to possess ACE2 receptors on the villous cytotrophoblast and the syncytiotrophoblast and findings suggest that the coronavirus enters the host cells via these ACE2 receptors.
The immune response in pregnancy increases the risk of contracting COVID-19.
Both normal pregnancy and COVID-19 are marked by decreased lymphocytes, NKG2A inhibitory receptors, and increased ACE2, IL-8, IL-10, and IP-10 it therefore safer to conclude that pregnancy is a risk factor for COVID-19 development.
Furthermore, the presence of the ACE2 receptors in the placenta may increase the risk of mother to baby transmission of the virus.
Therefore, more studies investigating the link between pregnancy and COVID-19 are needed.

Answer: {"verdict": "SUPPORT", "evidence": ["Pregnant women are more at risk of contracting COVID-19 due to their weakened immune system.", "Studies demonstrate that COVID-19 is an immune condition which is marked by reduced lymphocytes and elevated selected proinflammatory cytokines.", "Similar immune expression has been demonstrated in pregnancy by several studies."]}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: Covid-19 kills also young people

Abstract:
Objective: Severity of the coronavirus disease 2019 (covid-19) has been assessed in terms of absolute mortality in SARS-CoV-2 positive cohorts.
An assessment of mortality relative to mortality in the general population is presented.
Design: Retrospective population-based study.
Setting: Individual information on symptomatic confirmed SARS-CoV-2 patients and subsequent deaths from any cause were compared to the all-cause mortality in the Swiss population of 2018.
Starting February 23, 2020, mortality in covid-19 patients was monitored for 80 days and compared to the population mortality observed in the same time-of-year starting February 23, 2018.
Participants: 5 160 595 inhabitants of Switzerland aged 35 to 95 without covid-19 (general population in spring 2018) and 20 769 persons tested positively for covid-19 (spring 2020).
Measurements: Sex- and age-specific mortality rates were estimated using Cox proportional hazards models.
Absolute probabilities of death were predicted and risk was assessed in terms of relative mortality by taking the ratio between the sex- and age-specific absolute mortality in covid19 patients and the corresponding mortality in the 2018 general population.
Results: A confirmed SARS-CoV-2 infection substantially increased the probability of death across all patient groups, ranging from nine (6 to 15) times the population mortality in 35-year old infected females to a 53-fold increase (46 to 59) for 95 year old infected males.
The highest relative risks were observed among males and older patients.
The magnitude of these effects was smaller compared to increases observed in absolute mortality risk.
Male covid-19 patients exceeded the population hazard for males (hazard ratio 1.20, 1.00 to 1.44).
Each additional year of age increased the population hazard in covid-19 patients (hazard ratio 1.04, 1.03 to 1.05).
Limitations: Information about the distribution of relevant comorbidities was not available on population level and the associated risk was not quantified.
Conclusions: Health care professionals, decision makers, and societies are provided with an additional population-adjusted assessment of covid-19 mortality risk.
In combination with absolute measures of risk, the relative risks presented here help to develop a more comprehensive understanding of the actual impact of covid-19.

Answer: {"verdict": "SUPPORT", "evidence": ["Results: A confirmed SARS-CoV-2 infection substantially increased the probability of death across all patient groups, ranging from nine (6 to 15) times the population mortality in 35-year old infected females to a 53-fold increase (46 to 59) for 95 year old infected males.", "The highest relative risks were observed among males and older patients."]}


Question:
You will be shown a claim related to the COVID-19 pandemic, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT".
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract.

For instance, if the model were given the claim "the COVID vaccine is safe for healthy adults", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that the risks of severe COVID vaccine side effects are low for healthy adults."]
}

Claim: A booster dose enhances immunogenicity of the covid-19 vaccine candidate chadox1 ncov-19 in aged mice

Abstract:
The spread of SARS-CoV-2 has caused a global pandemic that has affected almost every aspect of human life.
The development of an effective COVID-19 vaccine could limit the morbidity and mortality caused by infection, and may enable the relaxation of social distancing measures.
Age is one of the most significant risk factors for poor health outcomes after SARS-CoV-2 infection, therefore it is desirable that any new vaccine candidates should elicit a robust immune response in older adults.
Here, we test the immunogenicity of the adenoviral vectored vaccine ChAdOx1 nCoV-19 (AZD-1222) in aged mice.
We find that a single dose of this vaccine induces cellular and humoral immunity in aged mice, but at a reduced magnitude than in younger adult mice.
Furthermore, we report that a second dose enhances the immune response to this vaccine in aged mice, indicating that a primeboost strategy may be a rational approach to enhance immunogenicity in older persons.

Answer: {"verdict": "SUPPORT", "evidence": ["We find that a single dose of this vaccine induces cellular and humoral immunity in aged mice, but at a reduced magnitude than in younger adult mice.", "Furthermore, we report that a second dose enhances the immune response to this vaccine in aged mice, indicating that a primeboost strategy may be a rational approach to enhance immunogenicity in older persons."]}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: Hypothesis: Angiotensin-converting enzyme inhibitors and angiotensin receptor blockers may increase the risk of severe COVID-19

Abstract:
The effects of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) on the risk of COVID-19 infection and disease progression are yet to be investigated.
The relationship between ACEI/ARB use and COVID-19 infection was systematically reviewed.
To identify relevant studies that met predetermined inclusion criteria, unrestricted searches of the PubMed, Embase, and Cochrane Library databases were conducted.
The search strategy included clinical date published until May 9, 2020.
Twelve articles involving more than 19,000 COVID-19 cases were included.
To estimate overall risk, random-effects models were adopted.
Our results showed that ACEI/ARB exposure was not associated with a higher risk of COVID-19 infection (OR = 0.99; 95 % CI, 0-1.04; P = 0.672).
Among those with COVID-19 infection, ACEI/ARB exposure was also not associated with a higher risk of having severe infection (OR = 0.98; 95 % CI, 0.87-1.09; P = 0.69) or mortality (OR = 0.73, 95 %CI, 0.5-1.07; P = 0.111).
However, ACEI/ARB exposure was associated with a lower risk of mortality compared to those on non-ACEI/ARB antihypertensive drugs (OR = 0.48, 95 % CI, 0.29-0.81; P = 0.006).
In conclusion, current evidence did not confirm the concern that ACEI/ARB exposure is harmful in patientswith COVID-19 infection.
This study supports the current guidelines that discourage discontinuation of ACEIs or ARBs in COVID-19 patients and the setting of the COVID-19 pandemic.

Answer: {"verdict": "CONTRADICT", "evidence": ["In conclusion, current evidence did not confirm the concern that ACEI/ARB exposure is harmful in patientswith COVID-19 infection.", "This study supports the current guidelines that discourage discontinuation of ACEIs or ARBs in COVID-19 patients and the setting of the COVID-19 pandemic."]}


Question:
You will be shown a claim related to the COVID-19 pandemic, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT".
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract.

For instance, if the model were given the claim "the COVID vaccine is safe for healthy adults", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that the risks of severe COVID vaccine side effects are low for healthy adults."]
}

Claim: Prrsv affects global patterns of covid-19 early outbreak dynamics

Abstract:
Environmental factors are well known to affect spatio-temporal patterns of infectious disease outbreaks, but whether the rapid spread of COVID-19 across the globe is related to local environmental conditions is highly debated.
We assessed the impact of environmental factors (temperature, humidity and air pollution) on the global patterns of COVID-19 early outbreak dynamics during January-May 2020, controlling for several key socio-economic factors and airport connections.
We showed that during the earliest phase of the global outbreak (January-March), COVID-19 growth rates were non-linearly related to climate, with fastest spread in regions with a mean temperature of ca.
5 °C, and in the most polluted regions.
However, environmental effects faded almost completely when considering later outbreaks, in keeping with the progressive enforcement of containment actions.
Accordingly, COVID-19 growth rates consistently decreased with stringent containment actions during both early and late outbreaks.
Our findings indicate that environmental drivers may have played a role in explaining the early variation among regions in disease spread.
With limited policy interventions, seasonal patterns of disease spread might emerge, with temperate regions of both hemispheres being most at risk of severe outbreaks during colder months.
Nevertheless, containment measures play a much stronger role and overwhelm impacts of environmental variation, highlighting the key role for policy interventions in curbing COVID-19 diffusion within a given region.
If the disease will become seasonal in the next years, information on environmental drivers of COVID-19 can be integrated with epidemiological models to inform forecasting of future outbreak risks and improve management plans.

Answer: {"verdict": "CONTRADICT", "evidence": ["We showed that during the earliest phase of the global outbreak (January-March), COVID-19 growth rates were non-linearly related to climate, with fastest spread in regions with a mean temperature of ca."]}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: wearing a mask  may offer some protection for the covid-19

Abstract:
The COVID‐19 pandemic caused by the novel coronavirus SARS‐CoV‐2 has claimed many lives worldwide.
Wearing medical masks or N95 masks (namely N95 respirators) can slow the virus spread and reduce the infection risk.
Reuse of these masks can minimize waste, protect the environment, and help to solve the current imminent shortage of masks.
Disinfection of used masks is needed for reuse of them with safety, but improper decontamination can damage the blocking structure of masks.
In this study, we demonstrated, using avian coronavirus of infectious bronchitis virus to mimic SARS‐CoV‐2, that medical masks and N95 masks remained their blocking efficacy after being steamed on boiling water even for 2 hours.
We also demonstrated that three brands of medical masks blocked over 99% viruses in aerosols.
The avian coronavirus was completely inactivated after being steamed for 5 minutes.
Together, this study suggested that medical masks are adequate for use on most social occasions, and both medical masks and N95 masks can be reused for a few days with steam decontamination between use.
This article is protected by copyright.
All rights reserved.

Answer: {"verdict": "SUPPORT", "evidence": ["Wearing medical masks or N95 masks (namely N95 respirators) can slow the virus spread and reduce the infection risk.", "We also demonstrated that three brands of medical masks blocked over 99% viruses in aerosols.", "The avian coronavirus was completely inactivated after being steamed for 5 minutes.", "Together, this study suggested that medical masks are adequate for use on most social occasions, and both medical masks and N95 masks can be reused for a few days with steam decontamination between use."]}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: The coronavirus came from the local wet market in China

Abstract:
A novel coronavirus (severe acute respiratory syndrome-CoV-2) that initially originated from Wuhan, China, in December 2019 has already caused a pandemic.
While this novel coronavirus disease (covid-19) frequently induces mild diseases, it has also generated severe diseases among certain populations, including older-aged individuals with underlying diseases, such as cardiovascular disease and diabetes.
As of 31 March 2020, a total of 9786 confirmed cases with covid-19 have been reported in South Korea.
South Korea has the highest diagnostic rate for covid-19, which has been the major contributor in overcoming this outbreak.
We are trying to reduce the reproduction number of covid-19 to less than one and eventually succeed in controlling this outbreak using methods such as contact tracing, quarantine, testing, isolation, social distancing and school closure.
This report aimed to describe the current situation of covid-19 in South Korea and our response to this outbreak.

Answer: {"verdict": "NEI", "evidence": []}


Question:
You will be shown a claim related to the COVID-19 pandemic, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT".
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract.

For instance, if the model were given the claim "the COVID vaccine is safe for healthy adults", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that the risks of severe COVID vaccine side effects are low for healthy adults."]
}

Claim: Synergism of tnf-α and ifn-γ triggers inflammatory cell death , tissue damage , and mortality in sars-cov-2 infection and cytokine shock syndromes

Abstract:
The COVID-19 pandemic has caused significant morbidity and mortality.
Currently, there is a critical shortage of proven treatment options and an urgent need to understand the pathogenesis of multi-organ failure and lung damage.
Cytokine storm is associated with severe inflammation and organ damage during COVID-19.
However, a detailed molecular pathway defining this cytokine storm is lacking, and gaining mechanistic understanding of how SARS-CoV-2 elicits a hyperactive inflammatory response is critical to develop effective therapeutics.
Of the multiple inflammatory cytokines produced by innate immune cells during SARS-CoV-2 infection, we found that the combined production of TNF-α and IFN-γ specifically induced inflammatory cell death, PANoptosis, characterized by gasdermin–mediated pyroptosis, caspase-8–mediated apoptosis, and MLKL–mediated necroptosis.
Deletion of pyroptosis, apoptosis, or necroptosis mediators individually was not sufficient to protect against cell death.
However, cells deficient in both RIPK3 and caspase-8 or RIPK3 and FADD were resistant to this cell death.
Mechanistically, the STAT1/IRF1 axis activated by TNF-α and IFN-γ co-treatment induced iNOS for the production of nitric oxide.
Pharmacological and genetic deletion of this pathway inhibited pyroptosis, apoptosis, and necroptosis in macrophages.
Moreover, inhibition of PANoptosis protected mice from TNF-α and IFN-γ–induced lethal cytokine shock that mirrors the pathological symptoms of COVID-19.
In vivo neutralization of both TNF-α and IFN-γ in multiple disease models associated with cytokine storm showed that this treatment provided substantial protection against not only SARS-CoV-2 infection, but also sepsis, hemophagocytic lymphohistiocytosis, and cytokine shock models, demonstrating the broad physiological relevance of this mechanism.
Collectively, our findings reveal that blocking the COVID-19 cytokine-mediated inflammatory cell death signaling pathway identified in this study may benefit patients with COVID-19 or other cytokine storm-driven syndromes by limiting inflammation and tissue damage.
The findings also provide a molecular and mechanistic description for the term cytokine storm.
Additionally, these results open new avenues for the treatment of other infectious and autoinflammatory diseases and cancers where TNF-α and IFN-γ synergism play key pathological roles.

Answer: {"verdict": "SUPPORT", "evidence": ["In vivo neutralization of both TNF-\u03b1 and IFN-\u03b3 in multiple disease models associated with cytokine storm showed that this treatment provided substantial protection against not only SARS-CoV-2 infection, but also sepsis, hemophagocytic lymphohistiocytosis, and cytokine shock models, demonstrating the broad physiological relevance of this mechanism."]}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: A new Chinese coronavirus, a cousin of the SARS virus, has infected hundreds since the outbreak began in Wuhan, China, in December.

Abstract:
A novel coronavirus (severe acute respiratory syndrome-CoV-2) that initially originated from Wuhan, China, in December 2019 has already caused a pandemic.
While this novel coronavirus disease (covid-19) frequently induces mild diseases, it has also generated severe diseases among certain populations, including older-aged individuals with underlying diseases, such as cardiovascular disease and diabetes.
As of 31 March 2020, a total of 9786 confirmed cases with covid-19 have been reported in South Korea.
South Korea has the highest diagnostic rate for covid-19, which has been the major contributor in overcoming this outbreak.
We are trying to reduce the reproduction number of covid-19 to less than one and eventually succeed in controlling this outbreak using methods such as contact tracing, quarantine, testing, isolation, social distancing and school closure.
This report aimed to describe the current situation of covid-19 in South Korea and our response to this outbreak.

Answer: {"verdict": "NEI", "evidence": []}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: Diabetes is generally known to weaken the immune system, making it harder to protect against viral infections like COVID-19.

Abstract:
AIMS: The 2019 novel coronavirus disease (COVID-19) emerged in Wuhan, China, and was characterized as a pandemic by the World Health Organization.
Diabetes is an established risk associated with poor clinical outcomes, but the association of diabetes with COVID-19 has not been reported yet.
METHODS: In this cohort study, we retrospectively reviewed 258 consecutive hospitalized COVID-19 patients with or without diabetes at the West Court of Union Hospital in Wuhan, China, recruited from January 29 to February 12, 2020.
The clinical features, treatment strategies and prognosis data were collected and analyzed.
Prognosis was followed up until March 12, 2020.
RESULTS: Of the 258 hospitalized patients (63 with diabetes) with COVID-19, the median age was 64 years (range 23-91), and 138 (53.5%) were male.
Common symptoms included fever (82.2%), dry cough (67.1%), polypnea (48.1%), and fatigue (38%).
Patients with diabetes had significantly higher leucocyte and neutrophil counts, and higher levels of fasting blood glucose, serum creatinine, urea nitrogen and creatine kinase isoenzyme MB at admission compared with those without diabetes.
COVID-19 patients with diabetes were more likely to develop severe or critical disease conditions with more complications, and had higher incidence rates of antibiotic therapy, non-invasive and invasive mechanical ventilation, and death (11.1% vs. 4.1%).
Cox proportional hazard model showed that diabetes (adjusted hazard ratio [aHR] = 3.64; 95% confidence interval [CI]: 1.09, 12.21) and fasting blood glucose (aHR = 1.19; 95% CI: 1.08, 1.31) were associated with the fatality due to COVID-19, adjusting for potential confounders.
CONCLUSIONS: Diabetes mellitus is associated with increased disease severity and a higher risk of mortality in patients with COVID-19.

Answer: {"verdict": "NEI", "evidence": []}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: Drinking hot ginger tea, with or without these additional ingredients, will cure COVID-19

Abstract:
OBJECTIVE To analyze the characteristics of YouTube videos in Spanish on the basic measures to prevent coronavirus disease 2019 (COVID-19).
METHODS On 18 March 2020, a search was conducted on YouTube using the terms "Prevencion Coronavirus" and "Prevencion COVID-19".
We studied the associations between the type of authorship and the country of publication with other variables (such as the number of likes and basic measures to prevent COVID-19 according to the World Health Organization, among others) with univariate analysis and a multiple logistic regression model.
RESULTS A total of 129 videos were evaluated; 37.2% were produced in Mexico (25.6%) and Spain (11.6%), and 56.6% were produced by mass media, including television and newspapers.
The most frequently reported basic preventive measure was hand washing (71.3%), and the least frequent was not touching the eyes, nose, and mouth (24.0%).
Hoaxes (such as eating garlic or citrus to prevent COVID-19) were detected in 15 videos (10.9%).
In terms of authorship, papers produced by health professionals had a higher probability of reporting hand hygiene (OR (95% CI) = 4.20 (1.17-15.09)) and respiratory hygiene (OR (95% CI) = 3.05 (1.22-7.62)) as preventive measures.
CONCLUSION Information from YouTube in Spanish on basic measures to prevent COVID-19 is usually not very complete and differs according to the type of authorship.
Our findings make it possible to guide Spanish-speaking users on the characteristics of the videos to be viewed in order to obtain reliable information.

Answer: {"verdict": "CONTRADICT", "evidence": ["Hoaxes (such as eating garlic or citrus to prevent COVID-19) were detected in 15 videos (10.9%)."]}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: High Blood Pressure Doesn't Seem To Raise COVID-19 Risk

Abstract:
Investigations reported that hypertension, diabetes, and cardiovascular diseases were the most prevalent comorbidities among the patients with coronavirus disease 2019 (COVID-19).
Hypertension appeared consistently as the most prevalent risk factors in COVID-19 patients.
Some investigations speculated about the association between renin-angiotensin-aldosterone system (RAAS) and susceptibility to COVID-19, as well as the relationship between RAAS inhibitors and increased mortality in these patients.
This raised concern about the potential association between hypertension (and its treatment) and propensity for COVID-19.
There are only a few follow-up studies that investigated the impact of comorbidities on outcome in these patients with conflicting findings.
Hypertension has been proven to be more prevalent in patients with an adverse outcome (admission in intensive care unit, use of mechanical ventilation, or death).
So far, there is no study that demonstrated independent predictive value of hypertension on mortality in COVID-19 patients.
There are many speculations about this coronavirus and its relation with different risk factors and underlying diseases.
The aim of this review was to summarize the current knowledge about the relationship between hypertension and COVID-19 and the role of hypertension on outcome in these patients.

Answer: {"verdict": "CONTRADICT", "evidence": ["Hypertension appeared consistently as the most prevalent risk factors in COVID-19 patients.", "Hypertension has been proven to be more prevalent in patients with an adverse outcome (admission in intensive care unit, use of mechanical ventilation, or death)."]}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: The most effective way to protect yourself against the new coronavirus is by frequently cleaning your hands with alcohol-based hand

Abstract:
Among the basic protective measures against COVID-19, the need to wash hands frequently and in a prolonged way using soap, and to regularly use alcohol-based hand sanitizers is well established for the whole population.
Healthcare workers in general, and particularly those involved in the direct care of COVID-19 patients, have to wear personal protective equipment (PPE) daily for many hours and also accomplish general preventive measurements outside their work.
Cutaneous adverse reactions can develop that need to be prevented, identified and therapeutically managed.
According to the data reported by Lin et al 1 , based in the experience from healthcare workers in Wuhan, adverse skin reactions were reported in 74% of responders (n=376) to a general survey.
The most commonly reported types of eruptions were skin dryness or desquamation (68.6%), papules or erythema (60.4%) and maceration (52,9%).

Answer: {"verdict": "SUPPORT", "evidence": ["Among the basic protective measures against COVID-19, the need to wash hands frequently and in a prolonged way using soap, and to regularly use alcohol-based hand sanitizers is well established for the whole population."]}


Question:
You will be shown a claim related to the COVID-19 pandemic, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT".
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract.

For instance, if the model were given the claim "the COVID vaccine is safe for healthy adults", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that the risks of severe COVID vaccine side effects are low for healthy adults."]
}

Claim: Seasonal human coronavirus antibodies are boosted upon sars-cov-2 infection but strongly associated with protection

Abstract:
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly spread within the human population.
Although SARS-CoV-2 is a novel coronavirus, most humans had been previously exposed to other antigenically distinct common seasonal human coronaviruses (hCoVs) before the COVID-19 pandemic.
Here, we quantified levels of SARS-CoV-2-reactive antibodies and hCoV-reactive antibodies in serum samples collected from 204 humans before the COVID-19 pandemic.
We then quantified pre-pandemic antibody levels in serum from a separate cohort of 252 individuals who became PCR-confirmed infected with SARS-CoV-2.
Finally, we longitudinally measured hCoV and SARS-CoV-2 antibodies in the serum of hospitalized COVID-19 patients.
Our studies indicate that most individuals possessed hCoV-reactive antibodies before the COVID-19 pandemic.
We determined that ~23% of these individuals possessed non-neutralizing antibodies that cross-reacted with SARS-CoV-2 spike and nucleocapsid proteins.
These antibodies were not associated with protection against SARS-CoV-2 infections or hospitalizations, but paradoxically these hCoV cross-reactive antibodies were boosted upon SARS-CoV-2 infection.

Answer: {"verdict": "CONTRADICT", "evidence": ["Although SARS-CoV-2 is a novel coronavirus, most humans had been previously exposed to other antigenically distinct common seasonal human coronaviruses (hCoVs) before the COVID-19 pandemic.", "We then quantified pre-pandemic antibody levels in serum from a separate cohort of 252 individuals who became PCR-confirmed infected with SARS-CoV-2.", "These antibodies were not associated with protection against SARS-CoV-2 infections or hospitalizations, but paradoxically these hCoV cross-reactive antibodies were boosted upon SARS-CoV-2 infection."]}


Question:
You will be shown a claim related to the COVID-19 pandemic, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT".
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract.

For instance, if the model were given the claim "the COVID vaccine is safe for healthy adults", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that the risks of severe COVID vaccine side effects are low for healthy adults."]
}

Claim: Hydroxychloroquine proves efficiently in hamsters and macaques infected with sars-cov-2

Abstract:
We remain largely without effective prophylactic/therapeutic interventions for COVID-19.
Although many human clinical trials are ongoing, there remains a deficiency of supportive preclinical drug efficacy studies.
Here we assessed the prophylactic/therapeutic efficacy of hydroxychloroquine (HCQ), a drug of interest for COVID-19 management, in two animal models.
When used for prophylaxis or treatment neither the standard human malaria dose (6.5 mg/kg) nor a high dose (50 mg/kg) of HCQ had any beneficial effect on clinical disease or SARS-CoV-2 kinetics (replication/shedding) in the Syrian hamster disease model.
Similarly, HCQ prophylaxis/treatment (6.5 mg/kg) did not significantly benefit clinical outcome nor reduce SARS-CoV-2 replication/shedding in the upper and lower respiratory tract in the rhesus macaque disease model.
In conclusion, our preclinical animal studies do not support the use of HCQ in prophylaxis/treatment of COVID-19.

Answer: {"verdict": "CONTRADICT", "evidence": ["Similarly, HCQ prophylaxis/treatment (6.5 mg/kg) did not significantly benefit clinical outcome nor reduce SARS-CoV-2 replication/shedding in the upper and lower respiratory tract in the rhesus macaque disease model."]}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: both dogs and cats can be infected by the virus that causes Covid-19 in humans, but none of the ten animals observed in the study showed clinical symptoms like coughing

Abstract:
On April 22, CDC and the U.S. Department of Agriculture (USDA) reported cases of two domestic cats with confirmed infection with SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19).
These are the first reported companion animals (including pets and service animals) with SARS-CoV-2 infection in the United States, and among the first findings of SARS-CoV-2 symptomatic companion animals reported worldwide.
These feline cases originated from separate households and were epidemiologically linked to suspected or confirmed human COVID-19 cases in their respective households.
Notification of presumptive positive animal test results triggered a One Health* investigation by state and federal partners, who determined that no further transmission events to other animals or persons had occurred.
Both cats fully recovered.
Although there is currently no evidence that animals play a substantial role in spreading COVID-19, CDC advises persons with suspected or confirmed COVID-19 to restrict contact with animals during their illness and to monitor any animals with confirmed SARS-CoV-2 infection and separate them from other persons and animals at home (1).

Answer: {"verdict": "SUPPORT", "evidence": ["Although there is currently no evidence that animals play a substantial role in spreading COVID-19, CDC advises persons with suspected or confirmed COVID-19 to restrict contact with animals during their illness and to monitor any animals with confirmed SARS-CoV-2 infection and separate them from other persons and animals at home (1)."]}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: Some herbal medicine advocates believe that the combination of garlic, ginger and some herbs can cure Coronavirus.

Abstract:
In late December 2019 in Wuhan, China, several patients with viral pneumonia were identified as 2019 novel coronavirus (2019-nCoV).
So far, there are no specific treatments for patients with coronavirus disease-19 (COVID-19), and the treatments available today are based on previous experience with similar viruses such as severe acute respiratory syndrome-related coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and Influenza virus.
In this article, we have tried to reach a therapeutic window of drugs available to patients with COVID-19.
Cathepsin L is required for entry of the 2019-nCoV virus into the cell as target teicoplanin inhibits virus replication.
Angiotensin-converting-enzyme 2 (ACE2) in soluble form as a recombinant protein can prevent the spread of coronavirus by restricting binding and entry.
In patients with COVID-19, hydroxychloroquine decreases the inflammatory response and cytokine storm, but overdose causes toxicity and mortality.
Neuraminidase inhibitors such as oseltamivir, peramivir, and zanamivir are invalid for 2019-nCoV and are not recommended for treatment but protease inhibitors such as lopinavir/ritonavir (LPV/r) inhibit the progression of MERS-CoV disease and can be useful for patients of COVID-19 and, in combination with Arbidol, has a direct antiviral effect on early replication of SARS-CoV. Ribavirin reduces hemoglobin concentrations in respiratory patients, and remdesivir improves respiratory symptoms.
Use of ribavirin in combination with LPV/r in patients with SARS-CoV reduces acute respiratory distress syndrome and mortality, which has a significant protective effect with the addition of corticosteroids.
Favipiravir increases clinical recovery and reduces respiratory problems and has a stronger antiviral effect than LPV/r.
currently, appropriate treatment for patients with COVID-19 is an ACE2 inhibitor and a clinical problem reducing agent such as favipiravir in addition to hydroxychloroquine and corticosteroids.

Answer: {"verdict": "CONTRADICT", "evidence": ["In late December 2019 in Wuhan, China, several patients with viral pneumonia were identified as 2019 novel coronavirus (2019-nCoV).", "So far, there are no specific treatments for patients with coronavirus disease-19 (COVID-19), and the treatments available today are based on previous experience with similar viruses such as severe acute respiratory syndrome-related coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and Influenza virus."]}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: Nonsteroidal anti-inflammatory drugs (NSAIDs), such as ibuprofen, aspirin, and Advil, reduce fever, pain, and inflammation.

Abstract:
: The COVID-19 pandemic is challenging our cardiovascular care of patients with heart diseases.
In the setting of pericardial diseases, there are two possible different scenarios to consider: the patient being treated for pericarditis who subsequently becomes infected with SARS-CoV-2, and the patient with COVID-19 who develops pericarditis or pericardial effusion.
In both conditions, clinicians may be doubtful regarding the safety of nonsteroidal anti-inflammatory drugs (NSAIDs), corticosteroids, colchicine, and biological agents, such as anti-IL1 agents (e.g. anakinra), that are the mainstay of therapy for pericarditis.
For NSAIDs, there is no clear scientific evidence linking ibuprofen and other NSAIDs to worsening of COVID-19; however, it seems prudent to continue them, if necessary to control pericarditis, and on the other hand, to prefer paracetamol for fever and systemic symptoms related to COVID-19.
Treatments with corticosteroids, colchicine, and anakinra appear well tolerated in the context of COVID-19 infection and are currently actively evaluated as potential therapeutic options for COVID infection at different stages of the disease.
On this basis, currently most treatments for pericarditis do not appear contraindicated also in the presence of possible COVID-19 infection and should not be discontinued, and some (corticosteroids, colchicine, and anakinra) can be considered to treat both conditions.

Answer: {"verdict": "SUPPORT", "evidence": ["For NSAIDs, there is no clear scientific evidence linking ibuprofen and other NSAIDs to worsening of COVID-19; however, it seems prudent to continue them, if necessary to control pericarditis, and on the other hand, to prefer paracetamol for fever and systemic symptoms related to COVID-19."]}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: Scientists believe cannabis could help prevent, treat coronavirus

Abstract:
The recently discovered novel coronavirus, SARS-CoV-2 (COVID-19 virus), has brought the whole world to standstill with critical challenges, affecting both health and economic sectors worldwide.
Although initially, this pandemic was associated with causing severe pulmonary and respiratory disorders, recent case studies reported the association of cerebrovascular-neurological dysfunction in COVID-19 patients, which is also life-threatening.
Several SARS-CoV-2 positive case studies have been reported where there are mild or no symptoms of this virus.
However, a selection of patients are suffering from large artery ischemic strokes.
Although the pathophysiology of the SARS-CoV-2 virus affecting the cerebrovascular system has not been elucidated yet, researchers have identified several pathogenic mechanisms, including a role for the ACE2 receptor.
Therefore, it is extremely crucial to identify the risk factors related to the progression and adverse outcome of cerebrovascular-neurological dysfunction in COVID-19 patients.
Since many articles have reported the effect of smoking (tobacco and cannabis) and vaping in cerebrovascular and neurological systems, and considering that smokers are more prone to viral and bacterial infection compared to non-smokers, it is high time to explore the probable correlation of smoking in COVID-19 patients.
Herein, we have reviewed the possible role of smoking and vaping on cerebrovascular and neurological dysfunction in COVID-19 patients, along with potential pathogenic mechanisms associated with it.

Answer: {"verdict": "CONTRADICT", "evidence": ["Since many articles have reported the effect of smoking (tobacco and cannabis) and vaping in cerebrovascular and neurological systems, and considering that smokers are more prone to viral and bacterial infection compared to non-smokers, it is high time to explore the probable correlation of smoking in COVID-19 patients."]}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: No drug is approved by the Food and Drug Administration (FDA) for COVID-19, although dozens of candidates - including drugs used to treat rheumatoid arthritis, parasites, cancer, and HIV - have been proposed

Abstract:
The SARS-CoV-2 virus emerged in December 2019 and then spread rapidly worldwide, particularly to China, Japan, and South Korea.
Scientists are endeavoring to find antivirals specific to the virus.
Several drugs such as chloroquine, arbidol, remdesivir, and favipiravir are currently undergoing clinical studies to test their efficacy and safety in the treatment of coronavirus disease 2019 (COVID-19) in China; some promising results have been achieved thus far.
This article summarizes agents with potential efficacy against SARS-CoV-2.

Answer: {"verdict": "SUPPORT", "evidence": ["Scientists are endeavoring to find antivirals specific to the virus.", "Several drugs such as chloroquine, arbidol, remdesivir, and favipiravir are currently undergoing clinical studies to test their efficacy and safety in the treatment of coronavirus disease 2019 (COVID-19) in China; some promising results have been achieved thus far."]}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: There is also evidence that smokers in hospital who have coronavirus are at a higher risk than non-smokers of severe illness and death. While it's important to prevent getting COVID-19 in the first place, it's also essential that we do all we can to keep our lungs healthy to avoid the worst affects of the disease.

Abstract:
Some comorbidities are associated with severe coronavirus disease (Covid-19) but it is unclear whether some increase susceptibility to Covid-19.
In this case-control Mexican study we found that obesity represents the strongest predictor for Covid-19 followed by diabetes and hypertension in both sexes and chronic renal failure in females only.
Active smoking was associated with decreased odds of Covid-19.
These findings indicate that these comorbidities are not only associated with severity of disease but also predispose for getting Covid-19.
Future research is needed to establish the mechanisms involved in each comorbidity and the apparent "protective" effect of cigarette smoking.

Answer: {"verdict": "NEI", "evidence": []}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: Coronavirus remains stable on metals and plastic for three days. Outside a lab, however, the virus might last considerably longer: its genetic material could be detected on surfaces 17 days after a cruise ship was empty of passengers (although it's not clear whether that material represents infectious virus particles).

Abstract:
The ocular surface has been suggested as a site of infection with Coronavirus-2 (SARS-CoV-2) responsible for the coronavirus disease-19 (COVID-19).
This review examines the evidence for this hypothesis, and its implications for clinical practice.
Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), responsible for the COVID-19 pandemic, is transmitted by person-to-person contact, via airborne droplets, or through contact with contaminated surfaces.
SARS-CoV-2 binds to angiotensin converting enzyme-2 (ACE2) to facilitate infection in humans.
This review sets out to evaluate evidence for the ocular surface as a route of infection.
A literature search in this area was conducted on 15 April 2020 using the Scopus database.
In total, 287 results were returned and reviewed.
There is preliminary evidence for ACE2 expression on corneal and conjunctival cells, but most of the other receptors to which coronaviruses bind appear to be found under epithelia of the ocular surface.
Evidence from animal studies is limited, with a single study suggesting viral particles on the eye can travel to the lung, resulting in very mild infection.
Coronavirus infection is rarely associated with conjunctivitis, with occasional cases reported in patients with confirmed COVID-19, along with isolated cases of conjunctivitis as a presenting sign.
Coronaviruses have been rarely isolated from tears or conjunctival swabs.
The evidence suggests coronaviruses are unlikely to bind to ocular surface cells to initiate infection.
Additionally, hypotheses that the virus could travel from the nasopharynx or through the conjunctival capillaries to the ocular surface during infection are probably incorrect.
Conjunctivitis and isolation of the virus from the ocular surface occur only rarely, and overwhelmingly in patients with confirmed COVID-19.
Necessary precautions to prevent person-to-person transmission should be employed in clinical practice throughout the pandemic, and patients should be reminded to maintain good hygiene practices.

Answer: {"verdict": "NEI", "evidence": []}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: Dogs May Not Spread Covid-19, but Cats Can Pass It to Each Other

Abstract:
Coronavirus disease-19 (COVID-19) caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is now a pandemic threat.
This virus is supposed to be spread by human to human transmission.
Cellular angiotensin-converting enzyme 2 (ACE2) is the receptor of SARS-CoV-2 which is identical or similar in different species of animals such as pigs, ferrets, cats, orangutans, monkeys, and humans.
Moreover, a recent study predicted that dogs might be secondary hosts during the evolution of SARS-CoV-2 from bat to human.
Therefore, there is a possibility of spreading SARS-CoV-2 through domestic pets.
There are now many reports of SARS-CoV-2 positive cases in dogs, cats, tigers, lion, and minks.
Experimental data showed ferrets and cats are highly susceptible to SARS-CoV-2 as infected by virus inoculation and can transmit the virus directly or indirectly by droplets or airborne routes.
Based on these natural infection reports and experimental data, whether the pets are responsible for SARS-CoV-2 spread to humans; needs to be deeply investigated.
Humans showing clinical symptoms of respiratory infections have been undergoing for the COVID-19 diagnostic test but many infected people and few pets confirmed with SARS-CoV-2 remained asymptomatic.
In this review, we summarize the natural cases of SARS-CoV-2 in animals with the latest researches conducted in this field.
This review will be helpful to think insights of SARS-CoV-2 transmissions, spread, and demand for seroprevalence studies, especially in companion animals.

Answer: {"verdict": "CONTRADICT", "evidence": ["Coronavirus disease-19 (COVID-19) caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is now a pandemic threat.", "This virus is supposed to be spread by human to human transmission."]}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: throwing hot water on ginger as a cure-all for COVID-19

Abstract:
OBJECTIVE To analyze the characteristics of YouTube videos in Spanish on the basic measures to prevent coronavirus disease 2019 (COVID-19).
METHODS On 18 March 2020, a search was conducted on YouTube using the terms "Prevencion Coronavirus" and "Prevencion COVID-19".
We studied the associations between the type of authorship and the country of publication with other variables (such as the number of likes and basic measures to prevent COVID-19 according to the World Health Organization, among others) with univariate analysis and a multiple logistic regression model.
RESULTS A total of 129 videos were evaluated; 37.2% were produced in Mexico (25.6%) and Spain (11.6%), and 56.6% were produced by mass media, including television and newspapers.
The most frequently reported basic preventive measure was hand washing (71.3%), and the least frequent was not touching the eyes, nose, and mouth (24.0%).
Hoaxes (such as eating garlic or citrus to prevent COVID-19) were detected in 15 videos (10.9%).
In terms of authorship, papers produced by health professionals had a higher probability of reporting hand hygiene (OR (95% CI) = 4.20 (1.17-15.09)) and respiratory hygiene (OR (95% CI) = 3.05 (1.22-7.62)) as preventive measures.
CONCLUSION Information from YouTube in Spanish on basic measures to prevent COVID-19 is usually not very complete and differs according to the type of authorship.
Our findings make it possible to guide Spanish-speaking users on the characteristics of the videos to be viewed in order to obtain reliable information.

Answer: {"verdict": "CONTRADICT", "evidence": ["Hoaxes (such as eating garlic or citrus to prevent COVID-19) were detected in 15 videos (10.9%)."]}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: No, garlic doesn't cure coronavirus.

Abstract:
The severity of coronavirus disease 2019 (COVID-19) infection is quite variable and the manifestations varies from asymptomatic disease to severe acute respiratory infection.
Fever, dry cough, dyspnea, myalgia, fatigue, loss of appetite, olfactory and gustatory dysfunctions are the most prevalent general symptoms.
Decreased immune system cells such as suppressed regulatory T cells, cytotoxic and helper T cells, natural killer cells, monocytes/macrophages and increased proinflammatory cytokines are the characteristic features.
Compounds derived from Allium sativum (garlic) have the potential to decrease the expression of proinflammatory cytokines and to reverse the immunological abnormalities to more acceptable levels.
Allium sativum is suggested as a beneficial preventive measure before being infected with SARS-CoV-2 virus.
Allium sativum is a functional food well-known for its immunomodulatory, antimicrobial, antiinflammatory, antimutagenic, antitumor properties.
Its antiviral efficiency was also demonstrated.
Some constituents of this plant were found to be active against protozoan parasites.
Within this context, it appears to reverse most immune system dysfunctions observed in patients with COVID-19 infection.
The relations among immune system parameters, leptin, leptin receptor, adenosin mono phosphate-activated protein kinase, peroxisome proliferator activated receptor-gamma have also been interpreted.
Leptin's role in boosting proinflammatory cytokines and in appetite decreasing suggest the possible beneficial effect of decreasing the concentration of this proinflammatory adipose tissue hormone in relieving some symptoms detected during COVID-19 infection.
In conclusion, Allium sativum may be an acceptable preventive measure against COVID-19 infection to boost immune system cells and to repress the production and secretion of proinflammatory cytokines as well as an adipose tissue derived hormone leptin having the proinflammatory nature.

Answer: {"verdict": "SUPPORT", "evidence": ["In conclusion, Allium sativum may be an acceptable preventive measure against COVID-19 infection to boost immune system cells and to repress the production and secretion of proinflammatory cytokines as well as an adipose tissue derived hormone leptin having the proinflammatory nature."]}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: there are few novel sars-cov-2 cases in malaria countries because of the use of the antimalarial drug hydroxychloroquine.

Abstract:
Hydroxychloroquine (HCQ) has sparked much interest in the therapeutics of the Coronavirus Disease 2019 (COVID-19) pandemic.
Its antiviral properties have been studied for years; regarding the Severe Acute Respiratory Syndrome-Corona Virus-2 (SARS-CoV-2), it has been shown that HCQ may act at multiple levels.
These extend from the initial attachment of the virus to the respiratory epithelium to the inhibition of its replication by the alkalinisation of the phagolysosome's microenvironment and the post-translational modification of certain viral proteins.
Preliminary clinical evidence from China and France showed significant virological and clinical benefit in HCQ-treated patients, while other studies, mostly including critically ill patients, did not show favorable results.
In this review, we critically appraise the existing evidence on HCQ against SARS-CoV-2 with particular emphasis on its protective and therapeutic role.
Safety concerns that are relevant to the short-term HCQ use are also discussed.
In the context of the rapid evolution of the COVID-19 pandemic that strains the health care systems worldwide and considering limited population-wide testing rates in most of the vulnerable countries, early empiric short-term administration of HCQ in symptomatic individuals, may be a promising, safe and low-cost strategy.

Answer: {"verdict": "SUPPORT", "evidence": ["In the context of the rapid evolution of the COVID-19 pandemic that strains the health care systems worldwide and considering limited population-wide testing rates in most of the vulnerable countries, early empiric short-term administration of HCQ in symptomatic individuals, may be a promising, safe and low-cost strategy."]}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: Scientists are endeavoring to find antivirals specific to the virus. Several drugs such as chloroquine, arbidol, remdesivir, and favipiravir are currently undergoing clinical studies to test their efficacy and safety in the treatment of coronavirus disease 2019 (COVID-19) in China; some promising results have been achieved thus far.

Abstract:
The SARS-CoV-2 virus emerged in December 2019 and then spread rapidly worldwide, particularly to China, Japan, and South Korea.
Scientists are endeavoring to find antivirals specific to the virus.
Several drugs such as chloroquine, arbidol, remdesivir, and favipiravir are currently undergoing clinical studies to test their efficacy and safety in the treatment of coronavirus disease 2019 (COVID-19) in China; some promising results have been achieved thus far.
This article summarizes agents with potential efficacy against SARS-CoV-2.

Answer: {"verdict": "SUPPORT", "evidence": ["Scientists are endeavoring to find antivirals specific to the virus.", "Several drugs such as chloroquine, arbidol, remdesivir, and favipiravir are currently undergoing clinical studies to test their efficacy and safety in the treatment of coronavirus disease 2019 (COVID-19) in China; some promising results have been achieved thus far."]}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: SARS-CoV-2 originally jumped from animals to humans. So too did the virus responsible for SARS and MERS.

Abstract:
Little information on the SARS-CoV-2 virus in animals is available to date.
Whereas no one husbandry animal case has been reported to date, which would have significant implications in food safety, companion animals play a role in COVID-19 epidemiology that opens up new questions.
There is evidence that SARS-CoV-2 can infect felines, dogs and minks, and there is evidence of human-to-animal infection.
Likewise, the S protein nucleotide sequence of the SARS-CoV-2 virus isolated in domestic animals and humans is identical, and the replication of the SARS-CoV-2 in cats is efficient.
Besides, the epidemiological evidence for this current pandemic indicates that the spillover to humans was associated with close contact between man and exotic animals, very probably in Chinese wet markets, thus there is a growing general consensus that the exotic animal markets, should be strictly regulated.
The examination of these findings and the particular role of animals in COVID-19 should be carefully analyzed in order to establish preparation and containment measures.
Animal management and epidemiological surveillance must be also considered for COVID-19 control, and it can open up new questions regarding COVID-19 epidemiology and the role that animals play in it.

Answer: {"verdict": "NEI", "evidence": []}


Question:
You will be shown a claim about public health, and the abstract of a biomedical research paper. Each sentence from the abstract will be on a separate line. Your task is to return a JSON object with two fields:

- "verdict": The fact-checking verdict. If the information in the abstract supports the claim, write "SUPPORT". If the abstract contradicts the claim, write "CONTRADICT". If the abstract does not provide enough information to arrive at a verdict, write "NEI" (for "not enough information").
- "evidence": An array of sentences providing evidence for the verdict. Please copy all relevant sentences verbatim from the abstract. If the verdict was "NEI", then return an empty array.

For instance, if the model were given the claim "wearing masks can prevent the spread of COVID", the output might be
{
  "verdict": "SUPPORT",
  "evidence": ["Our findings indicate that mass mask-wearing reduces the transmission rate for COVID-19."]
}

Claim: Can acetaminophen (Tylenol) treat the coronavirus disease? No

Abstract:
BACKGROUND: Since there is still no definitive conclusion regarding which non-steroidal anti-inflammatory drugs (NSAIDs) are most effective and safe in viral respiratory infections, we decided to evaluate the efficacy and safety of various NSAIDs in viral respiratory infections so that we can reach a conclusion on which NSAID is best choice for coronavirus disease 2019 (COVID-19).
METHODS: A search was performed in Medline (via PubMed), Embase and CENTRAL databases until 23 March 2020.
Clinical trials on application of NSAIDs in viral respiratory infections were included.
RESULTS: Six clinical trials were included.
No clinical trial has been performed on COVID-19, Severe Acute Respiratory Syndrome and Middle East Respiratory Syndrome infections.
Studies show that ibuprofen and naproxen not only have positive effects in controlling cold symptoms, but also do not cause serious side effects in rhinovirus infections.
In addition, it was found that clarithromycin, naproxen and oseltamivir combination leads to decrease in mortality rate and duration of hospitalisation in patients with pneumonia caused by influenza.
CONCLUSION: Although based on existing evidence, NSAIDs have been effective in treating respiratory infections caused by influenza and rhinovirus, since there is no clinical trial on COVID-19 and case-reports and clinical experiences are indicative of elongation of treatment duration and exacerbation of the clinical course of patients with COVID-19, it is recommended to use substitutes such as acetaminophen for controlling fever and inflammation and be cautious about using NSAIDs in management of COVID-19 patients until there are enough evidence.
Naproxen may be a good choice for future clinical trials.

Answer: {"verdict": "SUPPORT", "evidence": ["CONCLUSION: Although based on existing evidence, NSAIDs have been effective in treating respiratory infections caused by influenza and rhinovirus, since there is no clinical trial on COVID-19 and case-reports and clinical experiences are indicative of elongation of treatment duration and exacerbation of the clinical course of patients with COVID-19, it is recommended to use substitutes such as acetaminophen for controlling fever and inflammation and be cautious about using NSAIDs in management of COVID-19 patients until there are enough evidence."]}