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:  Saliva testing does depend on standard PCR technology, and it does require some manual labor in order to move it through

Abstract:
The outbreak of COVID-19 has taken a large number of lives since 2019 and the death toll continues to increase all over the world.
Recent data reports that about 27 lacs of people are infected with this virus till date and around 2 lacs are dead due to this pandemic.
The situation in India is no way better.
In India, almost all the states have become victim of this deadly pandemic.
Considering the enormous population in India, citizens here are facing acute shortage of detection kits and many are dying even before the knowledge of their infection.
The present treatise proposes a molecularly imprinted polymer (MIP) based technique for simple and rapid detection of COVID-19.
The technique will be inexpensive, selective, reusable and easy to handle.
It has been already implemented in our laboratory in order to detect the taste contributing agents found in tea.
This article discusses the detailed methodology and the resultant analytical characteristic of the sensors developed so far and also outlines the suitability of the MIP technique towards fabrication of testing kits for rapid detection of COVID-19.

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: The sars-cov-2 and other human coronavirus spike proteins are fine-tuned towards temperature and proteases of the human airways

Abstract:
The high transmissibility of SARS-CoV-2 is related to abundant replication in the upper airways, which is not observed for the other highly pathogenic coronaviruses SARS-CoV-1 and MERS-CoV. We here reveal features of the coronavirus spike (S) protein, which optimize the virus towards different parts of the respiratory tract.
First, the SARS-CoV-2 spike (SARS-2-S) reached higher levels in pseudoparticles when produced at 33°C instead of 37°C.
Even stronger preference for the upper airway temperature of 33°C was evident for the S protein of HCoV-229E, a common cold coronavirus.
In contrast, the S proteins of SARS-CoV-1 and MERS-CoV favored 37°C, in accordance with their preference for the lower airways.
Next, SARS-2-S proved efficiently activated by TMPRSS13, besides the previously identified host cell protease TMPRSS2, which may broaden the cell tropism of SARS-CoV-2.
TMPRSS13 was found to be an effective spike activator for the virulent coronaviruses but not the common cold HCoV-229E virus.
Activation by these proteases requires pre-cleavage of the SARS-2-S S1/S2 cleavage loop, and both its furin motif and extended loop length proved critical to achieve virus entry into airway epithelial cells.
Finally, we show that the D614G mutation in SARS-2-S increases S protein stability and expression at 37°C, and promotes virus entry via cathepsin B/L activation.
These spike properties might promote virus spread, potentially explaining why the G614 variant is currently predominating worldwide.
Collectively, our findings indicate how the coronavirus spike protein is fine-tuned towards the temperature and protease conditions of the airways, to enhance virus transmission and pathology.
SIGNIFICANCE STATEMENT The rapid spread of SARS-CoV-2, the cause of COVID-19, is related to abundant replication in the upper airways, which is not observed for other highly pathogenic human coronaviruses.
We here reveal features of the coronavirus spike (S) protein, which optimize the virus towards different parts of the respiratory tract.
Coronavirus spikes exhibit distinct temperature preference to precisely match the upper (~33°C) or lower (37°C) airways.
We identified airway proteases that activate the spike for virus entry into cells, including one protease that may mediate coronavirus virulence.
Also, a link was seen between spike stability and entry via endosomal proteases.
This mechanism of spike fine-tuning could explain why the SARS-CoV-2 spike-D614G mutant is more transmissible and therefore globally predominant.

Answer: {"verdict": "SUPPORT", "evidence": ["The high transmissibility of SARS-CoV-2 is related to abundant replication in the upper airways, which is not observed for the other highly pathogenic coronaviruses SARS-CoV-1 and MERS-CoV. We here reveal features of the coronavirus spike (S) protein, which optimize the virus towards different parts of the respiratory tract.", "Even stronger preference for the upper airway temperature of 33\u00b0C was evident for the S protein of HCoV-229E, a common cold coronavirus.", "Collectively, our findings indicate how the coronavirus spike protein is fine-tuned towards the temperature and protease conditions of the airways, to enhance virus transmission and pathology.", "SIGNIFICANCE STATEMENT The rapid spread of SARS-CoV-2, the cause of COVID-19, is related to abundant replication in the upper airways, which is not observed for other highly pathogenic human coronaviruses.", "Coronavirus spikes exhibit distinct temperature preference to precisely match the upper (~33\u00b0C) or lower (37\u00b0C) airways."]}


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: Widely available lysosome targeting agents should be considered as a potential marker for covid-19

Abstract:
While the COVID-19 pandemic advances, the scientific community struggles in the search for treatments.
Several improvements have been made, including the discovery of clinical efficacy of chloroquine (CQ) in COVID-19 patients, but the effective treatment protocols are still missing.
In order to find novel treatment options many scientists utilize the in silico approach to identify compounds that could interfere with the key molecules involved in entrance, replication, or dissemination of the SARS-CoV-2.
However, most of the identified molecules are currently not available as pharmacological agents, and assessing their safety and efficacy could take many months.
Here, we took a different approach based on the proposed pharmacodynamic model of CQ in COVID-19.
The main mechanism of action responsible for the favourable outcome of COVID-19 patients treated with CQ seems to be related to pH modulation-mediated effect on the endolysosomal trafficking, a characteristic of chemical compounds often called lysosomotropic agents because of the physico-chemical properties that enable them to passively diffuse through the endosomal membrane and undergo protonation-based trapping in the lumen of the acidic vesicles.
In this review, we discuss lysosomotropic and lysosome targeting drugs that are already in clinical use and are characterized by good safety profiles, low cost, and wide availability.
We emphasize that some of these drugs, in particular azithromycin and other macrolide antibiotics, indomethacin and some other non-steroidal anti-inflammatory drugs, proton pump inhibitors, and fluoxetine could provide additional therapeutic benefits in addition to the potential antiviral effect that still has to be confirmed by well-controlled clinical trials.
As some of these drugs, mostly antibiotics, were already empirically used in the treatment of COVID-19, we encourage our colleagues all over the world to publish patient data so potential efficacy of these agents can be evaluated in the clinical context and rapidly implemented in the therapeutic protocols if the beneficial effect on clinical outcome is observed.

Answer: {"verdict": "CONTRADICT", "evidence": ["The main mechanism of action responsible for the favourable outcome of COVID-19 patients treated with CQ seems to be related to pH modulation-mediated effect on the endolysosomal trafficking, a characteristic of chemical compounds often called lysosomotropic agents because of the physico-chemical properties that enable them to passively diffuse through the endosomal membrane and undergo protonation-based trapping in the lumen of the acidic vesicles.", "As some of these drugs, mostly antibiotics, were already empirically used in the treatment of COVID-19, we encourage our colleagues all over the world to publish patient data so potential efficacy of these agents can be evaluated in the clinical context and rapidly implemented in the therapeutic protocols if the beneficial effect on clinical outcome is observed."]}


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 potently neutralizing antibody protects cells against sars-cov-2 infection

Abstract:
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for millions of infections and hundreds of thousands of deaths globally.
There are no widely available licensed therapeutics against SARS-CoV-2, highlighting an urgent need for effective interventions.
The virus enters host cells through binding of a receptor-binding domain within its trimeric spike glycoprotein to human angiotensin-converting enzyme 2.
In this article, we describe the generation and characterization of a panel of murine mAbs directed against the receptor-binding domain.
One mAb, 2B04, neutralized wild-type SARS-CoV-2 in vitro with remarkable potency (half-maximal inhibitory concentration of <2 ng/ml).
In a murine model of SARS-CoV-2 infection, 2B04 protected challenged animals from weight loss, reduced lung viral load, and blocked systemic dissemination.
Thus, 2B04 is a promising candidate for an effective antiviral that can be used to prevent SARS-CoV-2 infection.

Answer: {"verdict": "CONTRADICT", "evidence": ["In a murine model of SARS-CoV-2 infection, 2B04 protected challenged animals from weight loss, reduced lung viral load, and blocked systemic dissemination."]}


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 high temperature and low relative humidity lead to high evaporation rates of saliva-contaminated droplets, thus significantly reducing the coronavirus viability

Abstract:
The coronavirus disease 2019 (COVID-19) outbreak has become a severe public health issue.
The novelty of the virus prompts a search for understanding of how ecological factors affect the transmission and survival of the virus.
Several studies have robustly identified a relationship between temperature and the number of cases.
However, there is no specific study for a tropical climate such as Brazil.
This work aims to determine the relationship of temperature to COVID-19 infection for the state capital cities of Brazil.
Cumulative data with the daily number of confirmed cases was collected from February 27 to April 1, 2020, for all 27 state capital cities of Brazil affected by COVID-19.
A generalized additive model (GAM) was applied to explore the linear and nonlinear relationship between annual average temperature compensation and confirmed cases.
Also, a polynomial linear regression model was proposed to represent the behavior of the growth curve of COVID-19 in the capital cities of Brazil.
The GAM dose-response curve suggested a negative linear relationship between temperatures and daily cumulative confirmed cases of COVID-19 in the range from 16.8 °C to 27.4 °C.
Each 1 °C rise of temperature was associated with a -4.8951% (t = -2.29, p = 0.0226) decrease in the number of daily cumulative confirmed cases of COVID-19.
A sensitivity analysis assessed the robustness of the results of the model.
The predicted R-squared of the polynomial linear regression model was 0.81053.
In this study, which features the tropical temperatures of Brazil, the variation in annual average temperatures ranged from 16.8 °C to 27.4 °C.
Results indicated that temperatures had a negative linear relationship with the number of confirmed cases.
The curve flattened at a threshold of 25.8 °C.
There is no evidence supporting that the curve declined for temperatures above 25.8 °C.
The study had the goal of supporting governance for healthcare policymakers.

Answer: {"verdict": "CONTRADICT", "evidence": ["Results indicated that temperatures had a negative linear relationship with the number of confirmed cases."]}


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: Cell entry of sars-cov-2 conferred by angiotensin-converting enzyme 2 of different specie

Abstract:
The outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a huge threat to many countries around the world.
However, where is it origin and which animals are sensitive to cross-species transmission is unclear.
The interaction of virus and cell receptor is a key determinant of host range for the novel coronavirus.
Angiotensin-converting enzyme 2 (ACE2) is demonstrated as the primary entry receptor for SARS-CoV-2.
In this study, we evaluated the SARS-CoV-2 entry mediated by ACE2 of 11 different species of animals, and discovered that ACE2 of Rhinolophus sinicus (Chinese horseshoe bat), Felis catus (domestic cat), Canis lupus familiaris (dog), Sus scrofa (pig), Capra hircus (goat) and especially Manis javanica (Malayan pangolin) were able to render SARS-CoV-2 entry in non-susceptible cells.
This is the first report that ACE2 of Pangolin could mediate SARS-CoV-2 entry which increases the presume that SARS-CoV-2 may have a pangolin origin.
However, none of the ACE2 proteins from Rhinolophus ferrumequinum (greater horseshoe bat), Gallus gallus (chicken), Notechis scutatus (mainland tiger snake), Mus musculus (house mouse) rendered SARS-CoV-2 entry.
Specifically, a natural isoform of Macaca mulatta (Rhesus monkey) ACE2 with a mutation of Y217N was resistance to infection, which rises the possible impact of this type of ACE2 during monkey studies of SARS-CoV-2.
Overall, these results clarify that SARS-CoV-2 could engage receptors of multiple species of animals and it is a perplexed work to track SARS-CoV-2 origin and its intermediate hosts.
IMPORTANCE In this study, we illustrated that SARS-CoV-2 is able to engage receptors of multiple species of animals.
This indicated that it may be a perplexed work to track SARS-CoV-2 origin and discover its intermediate hosts.
This feature of virus is considered to potentiate its diverse cross-species transmissibility.
Of note, here is the first report that ACE2 of Pangolin could mediate SARS-CoV-2 entry which increases the possibility that SARS-CoV-2 may have a pangolin origin. And we also demonstrated that not all species of bat were sensitive to SARS-CoV-2 infection.
At last, it is also important to detect the expression ratio of the Y217N ACE2 to the prototype in Rhesus monkeys to be recruited for studies on SARS-CoV-2 infection.

Answer: {"verdict": "SUPPORT", "evidence": ["Angiotensin-converting enzyme 2 (ACE2) is demonstrated as the primary entry receptor for SARS-CoV-2."]}


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: Unfortunately, to date, no vaccines or antiviral drugs have been approved for the treatment of SARS-CoV-2 infection by regulatory agencies.

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": "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: Higher risk if you have type 1 diabetes. Compared to people without diabetes, people with type 1 diabetes are approximately 3.5 times as likely to die in hospital with COVID-19, while people with type 2 are approximately twice as likely.

Abstract:
AIMS: We aimed to briefly review the general characteristics of the novel coronavirus (SARS-CoV-2) and provide a better understanding of the coronavirus disease (COVID-19) in people with diabetes, and its management.
METHODS: We searched for articles in PubMed and Google Scholar databases till 02 April 2020, with the following keywords: "SARS-CoV-2", "COVID-19", "infection", "pathogenesis", "incubation period", "transmission", "clinical features", "diagnosis", "treatment", "diabetes", with interposition of the Boolean operator "AND".
RESULTS: The clinical spectrum of COVID-19 is heterogeneous, ranging from mild flu-like symptoms to acute respiratory distress syndrome, multiple organ failure and death.
Older age, diabetes and other comorbidities are reported as significant predictors of morbidity and mortality.
Chronic inflammation, increased coagulation activity, immune response impairment, and potential direct pancreatic damage by SARS-CoV-2 might be among the underlying mechanisms of the association between diabetes and COVID-19.
No conclusive evidence exists to support the discontinuation of angiotensin-converting enzyme inhibitors (ACEI), angiotensin receptor blockers or thiazolidinediones because of COVID-19 in people with diabetes.
Caution should be taken to potential hypoglycemic events with the use of chloroquine in these subjects.
Patient tailored therapeutic strategies, rigorous glucose monitoring and careful consideration of drug interactions might reduce adverse outcomes.
CONCLUSIONS: Suggestions are made on the possible pathophysiological mechanisms of the relationship between diabetes and COVID-19, and its management.
No definite conclusions can be made based on current limited evidence.
Further research regarding this relationship and its clinical management is warranted.

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: N95 masks are more effective than regular masks.

Abstract:
We present two models for the COVID-19 pandemic predicting the impact of universal face mask wearing upon the spread of the SARS-CoV-2 virus--one employing a stochastic dynamic network based compartmental SEIR (susceptible-exposed-infectious-recovered) approach, and the other employing individual ABM (agent-based modelling) Monte Carlo simulation--indicating (1) significant impact under (near) universal masking when at least 80% of a population is wearing masks, versus minimal impact when only 50% or less of the population is wearing masks, and (2) significant impact when universal masking is adopted early, by Day 50 of a regional outbreak, versus minimal impact when universal masking is adopted late.
These effects hold even at the lower filtering rates of homemade masks.
To validate these theoretical models, we compare their predictions against a new empirical data set we have collected that includes whether regions have universal masking cultures or policies, their daily case growth rates, and their percentage reduction from peak daily case growth rates.
Results show a near perfect correlation between early universal masking and successful suppression of daily case growth rates and/or reduction from peak daily case growth rates, as predicted by our theoretical simulations.
Our theoretical and empirical results argue for urgent implementation of universal masking.
As governments plan how to exit societal lockdowns, it is emerging as a key NPI; a"mouth-and-nose lockdown"is far more sustainable than a"full body lockdown", on economic, social, and mental health axes.
An interactive visualization of the ABM simulation is at http://dek.ai/masks4all.
We recommend immediate mask wearing recommendations, official guidelines for correct use, and awareness campaigns to shift masking mindsets away from pure self-protection, towards aspirational goals of responsibly protecting one's community.

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: Vitamin B could help prevent the 'worst outcomes' in covid-19 cases

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: there is no link between vitamin D concentrations and risk of COVID-19 infection.

Abstract:
The outbreak of COVID-19 has created a global public health crisis.
Little is known about the protective factors of this infection.
Therefore, preventive health measures that can reduce the risk of infection, progression and severity are desperately needed.
This review discussed the possible roles of vitamin D in reducing the risk of COVID-19 and other acute respiratory tract infections and severity.
Moreover, this study determined the correlation of vitamin D levels with COVID-19 cases and deaths in 20 European countries as of 20 May 2020.
A significant negative correlation (p=0.033) has been observed between mean vitamin D levels and COVID-19 cases per one million population in European countries.
However, the correlation of vitamin D with COVID-19 deaths of these countries was not significant.
Some retrospective studies demonstrated a correlation between vitamin D status and COVID-19 severity and mortality, while other studies did not find the correlation when confounding variables are adjusted.
Several studies demonstrated the role of vitamin D in reducing the risk of acute viral respiratory tract infections and pneumonia.
These include direct inhibition with viral replication or with anti-inflammatory or immunomodulatory ways.
In the meta-analysis, vitamin D supplementation has been shown as safe and effective against acute respiratory tract infections.
Thus, people who are at higher risk of vitamin D deficiency during this global pandemic should consider taking vitamin D supplements to maintain the circulating 25(OH)D in the optimal levels (75-125nmol/L).
In conclusion, there is not enough evidence on the association between vitamin D levels and COVID-19 severity and mortality.
Therefore, randomized control trials and cohort studies are necessary to test this hypothesis.

Answer: {"verdict": "CONTRADICT", "evidence": ["A significant negative correlation (p=0.033) has been observed between mean vitamin D levels and COVID-19 cases per one million population in European countries.", "Several studies demonstrated the role of vitamin D in reducing the risk of acute viral respiratory tract infections and pneumonia.", "These include direct inhibition with viral replication or with anti-inflammatory or immunomodulatory ways.", "In the meta-analysis, vitamin D supplementation has been shown as safe and effective against acute respiratory tract infections.", "Thus, people who are at higher risk of vitamin D deficiency during this global pandemic should consider taking vitamin D supplements to maintain the circulating 25(OH)D in the optimal levels (75-125nmol/L)."]}


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: Eating garlic will protect me against getting the coronavirus.

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: the virus can stay on surfaces long enough to be a source of transmission

Abstract:
The aim in this study was to assess the effectiveness of a quaternary ammonium chloride (QAC) surfactant in reducing surface staphylococcal contamination in a routinely operating medical ward occupied by patients who had tested positive for methicillin-resistant Staphylococcus aureus (MRSA).
The QAC being tested is an antibacterial film that is sprayed onto a surface and can remain active for up to 8 h. A field experimental study was designed with the QAC plus daily hypochlorite cleaning as the experimental group and hypochlorite cleaning alone as the control group.
The method of swabbing on moistened surfaces was used for sampling.
It was found that 83% and 77% of the bedside surfaces of MRSA-positive and MRSA-negative patients respectively were contaminated with staphylococci at 08:00 hours, and that the staphylococcal concentrations increased by 80% at 1200 h over a 4-hour period with routine ward and clinical activities.
Irrespective of the MRSA status of the patients, high-touch surfaces around the bed-units within the studied medical ward were heavily contaminated (ranged 1 to 276 cfu/cm(2) amongst the sites with positive culture) with staphylococcal bacteria including MRSA, despite the implementation of daily hypochlorite wiping.
However, the contamination rate dropped significantly from 78% to 11% after the application of the QAC polymer.
In the experimental group, the mean staphylococcal concentration of bedside surfaces was significantly (p < 0.0001) reduced from 4.4 ± 8.7 cfu/cm(2) at 08:00 hours to 0.07 ± 0.26 cfu/cm(2) at 12:00 hours by the QAC polymer.
The results of this study support the view that, in addition to hypochlorite wiping, the tested QAC surfactant is a potential environmental decontamination strategy for preventing the transmission of clinically important pathogens in medical wards.

Answer: {"verdict": "SUPPORT", "evidence": ["It was found that 83% and 77% of the bedside surfaces of MRSA-positive and MRSA-negative patients respectively were contaminated with staphylococci at 08:00 hours, and that the staphylococcal concentrations increased by 80% at 1200 h over a 4-hour period with routine ward and clinical activities."]}


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: Like other viruses with a lipid envelope, SARS-CoV-2 is probably sensitive to temperature, humidity, and solar radiation

Abstract:
This paper investigates the correlation between the high level of coronavirus SARS-CoV-2 infection accelerated transmission and lethality, and surface air pollution in Milan metropolitan area, Lombardy region in Italy.
For January-April 2020 period, time series of daily average inhalable gaseous pollutants ozone (O3) and nitrogen dioxide (NO2), together climate variables (air temperature, relative humidity, wind speed, precipitation rate, atmospheric pressure field and Planetary Boundary Layer) were analyzed.
In spite of being considered primarily transmitted by indoor bioaerosols droplets and infected surfaces or direct human-to-human personal contacts, it seems that high levels of urban air pollution, and climate conditions have a significant impact on SARS-CoV-2 diffusion.
Exhibited positive correlations of ambient ozone levels and negative correlations of NO2 with the increased rates of COVID-19 infections (Total number, Daily New positive and Total Deaths cases), can be attributed to airborne bioaerosols distribution.
The results show positive correlation of daily averaged O3 with air temperature and inversely correlations with relative humidity and precipitation rates.
Viral genome contains distinctive features, including a unique N-terminal fragment within the spike protein, which allows coronavirus attachment on ambient air pollutants.
At this moment it is not clear if through airborne diffusion, in the presence of outdoor and indoor aerosols, this protein "spike" of the new COVID-19 is involved in the infectious agent transmission from a reservoir to a susceptible host during the highest nosocomial outbreak in some agglomerated industrialized urban areas like Milan is.
Also, in spite of collected data for cold season (winter-early spring) period, when usually ozone levels have lower values than in summer, the findings of this study support possibility as O3 can acts as a COVID-19 virus incubator.
Being a novel pandemic coronavirus version, it might be ongoing during summer conditions associated with higher air temperatures, low relative humidity and precipitation levels.

Answer: {"verdict": "CONTRADICT", "evidence": ["Being a novel pandemic coronavirus version, it might be ongoing during summer conditions associated with higher air temperatures, low relative humidity and precipitation levels."]}


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: B cells and t cells mediate fusion to covid-19

Abstract:
Recent reports that antibodies to SARS-CoV-2 are not maintained in the serum following recovery from the virus have caused alarm.
However, the absence of specific antibodies in the serum does not necessarily mean an absence of immune memory.
Here, we discuss our current understanding of the relative contribution of B cells and T cells to immunity to SARS-CoV-2 and the implications for the development of effective treatments and vaccines for COVID-19.

Answer: {"verdict": "CONTRADICT", "evidence": ["Here, we discuss our current understanding of the relative contribution of B cells and T cells to immunity to SARS-CoV-2 and the implications for the development of effective treatments and vaccines for 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: there is no scientific evidence establishing a link between ibuprofen and worsening of covid-19

Abstract:
Ibuprofen is an over-the-counter medication that is used widely for the treatment of pain and fever during COVID-19 pandemic.
A concern was raised regarding the safety of ibuprofen use because of its role in increasing ACE2 levels within the Renin-Angiotensin-Aldosterone system.
ACE2 is the coreceptor for the entry of SARS-CoV-2 into cells, and so, a potential increased risk of contracting COVID-19 disease and/or worsening of COVID-19 infection was feared with ibuprofen use.
However, available data from limited studies show administration of recombinant ACE2 improves lung damage caused by respiratory viruses, suggesting ibuprofen use may be beneficial in COVID-19 disease.
At this time, there is no supporting evidence to discourage the use of ibuprofen.

Answer: {"verdict": "SUPPORT", "evidence": ["Ibuprofen is an over-the-counter medication that is used widely for the treatment of pain and fever during COVID-19 pandemic.", "However, available data from limited studies show administration of recombinant ACE2 improves lung damage caused by respiratory viruses, suggesting ibuprofen use may be beneficial in COVID-19 disease.", "At this time, there is no supporting evidence to discourage the use of ibuprofen."]}


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: However, some children can get severely ill from COVID-19. They might require hospitalization, intensive care, or a ventilator to help them breathe.

Abstract:
Background: As the novel coronavirus triggering COVID-19 has broken out in Wuhan, China and spread rapidly worldwide, it threatens the lives of thousands of people and poses a global threat on the economies of the entire world.
However, infection with COVID-19 is currently rare in children.
Objective To discuss the latest findings and research focus on the basis of characteristics of children confirmed with COVID-19, and provide an insight into the future treatment and research direction.
Methods: We searched the terms "COVID-19 OR coronavirus OR SARS-CoV-2" AND "Pediatric OR children" on PubMed, Embase, Cochrane library, NIH, CDC, and CNKI.
The authors also reviewed the guidelines published on Chinese CDC and Chinese NHC.
Results: We included 25 published literature references related to the epidemiology, clinical manifestation, accessary examination, treatment, and prognosis of pediatric patients with COVID-19.
Conclusion: The numbers of children with COVID-19 pneumonia infection are small, and most of them come from family aggregation.
Symptoms are mainly mild or even asymptomatic, which allow children to be a risk factor for transmission.
Thus, strict epidemiological history screening is needed for early diagnosis and segregation.
This holds especially for infants, who are more susceptible to infection than other age groups in pediatric age, but have most likely subtle and unspecific symptoms.
They need to be paid more attention to.
CT examination is a necessity for screening the suspected cases, because most of the pediatric patients are mild cases, and plain chest X-ray do not usually show the lesions or the detailed features.
Therefore, early chest CT examination combined with pathogenic detection is a recommended clinical diagnosis scheme in children.
The risk factors which may suggest severe or critical progress for children are: Fast respiratory rate and/or; lethargy and drowsiness mental state and/or; lactate progressively increasing and/or; imaging showed bilateral or multi lobed infiltration, pleural effusion or rapidly expending of lesions in a short period of time and/or; less than 3 months old or those who underly diseases.
For those critical pediatric patients with positive SARS-CoV-2 diagnosis, polypnea may be the most common symptom.
For treatment, the elevated PCT seen in children in contrast to adults suggests that the underlying coinfection/secondary infection may be more common in pediatric patients and appropriate antibacterial treatment should be considered.
Once cytokine storm is found in these patients, anti-autoimmune or blood-purifying therapy should be given in time.
Furthermore, effective isolation measures and appropriate psychological comfort need to be provided timely.

Answer: {"verdict": "CONTRADICT", "evidence": ["Conclusion: The numbers of children with COVID-19 pneumonia infection are small, and most of them come from family aggregation.", "Symptoms are mainly mild or even asymptomatic, which allow children to be a risk factor for 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: Surgical Masks Stop Transmission Of COVID-19 From Symptomatic People

Abstract:
OBJECTIVES: To determine the risk of SARS-CoV-2 transmission by aerosols, to provide evidence on the rational use of masks, and to discuss additional measures important for the protection of healthcare workers from COVID-19.
METHODS: Literature review and expert opinion.
SHORT CONCLUSION: SARS-CoV-2, the pathogen causing COVID-19, is considered to be transmitted via droplets rather than aerosols, but droplets with strong directional airflow support may spread further than 2 m. High rates of COVID-19 infections in healthcare-workers (HCWs) have been reported from several countries.
Respirators such as filtering face piece (FFP) 2 masks were designed to protect HCWs, while surgical masks were originally intended to protect patients (e.g., during surgery).
Nevertheless, high quality standard surgical masks (type II/IIR according to European Norm EN 14683) appear to be as effective as FFP2 masks in preventing droplet-associated viral infections of HCWs as reported from influenza or SARS.
So far, no head-to-head trials with these masks have been published for COVID-19.
Neither mask type completely prevents transmission, which may be due to inappropriate handling and alternative transmission pathways.
Therefore, compliance with a bundle of infection control measures including thorough hand hygiene is key.
During high-risk procedures, both droplets and aerosols may be produced, reason why respirators are indicated for these interventions.

Answer: {"verdict": "CONTRADICT", "evidence": ["Respirators such as filtering face piece (FFP) 2 masks were designed to protect HCWs, while surgical masks were originally intended to protect patients (e.g., during surgery).", "Nevertheless, high quality standard surgical masks (type II/IIR according to European Norm EN 14683) appear to be as effective as FFP2 masks in preventing droplet-associated viral infections of HCWs as reported from influenza or SARS."]}


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 unique covid-19 immune signature combines immuno-protection with discrete sepsis-like traits associated with poor prognosis

Abstract:
Person-to-person transmission of SARS-CoV-2 virus has triggered a global emergency because of its potential to cause life-threatening Covid-19 disease.
By comparison to pauci-symptomatic virus clearance by most individuals, Covid-19 has been proposed to reflect insufficient and/or pathologically exaggerated immune responses.
Here we identify a consensus peripheral blood immune signature across 63 hospital-treated Covid-19 patients who were otherwise highly heterogeneous.
The core signature conspicuously blended adaptive B cell responses typical of virus infection or vaccination with discrete traits hitherto associated with sepsis, including monocyte and dendritic cell dampening, and hyperactivation and depletion of discrete T cell subsets.
This blending of immuno-protective and immuno-pathogenic potentials was exemplified by near-universal CXCL10/IP10 upregulation, as occurred in SARS1 and MERS.
Moreover, specific parameters including CXCL10/IP10 over-expression, T cell proliferation, and basophil and plasmacytoid dendritic cell depletion correlated, often prognostically, with Covid-19 progression, collectively composing a resource to inform SARS-CoV-2 pathobiology and risk-based patient stratification.

Answer: {"verdict": "CONTRADICT", "evidence": ["The core signature conspicuously blended adaptive B cell responses typical of virus infection or vaccination with discrete traits hitherto associated with sepsis, including monocyte and dendritic cell dampening, and hyperactivation and depletion of discrete T cell subsets."]}


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 new coronavirus can damage the lungs, heart and brain, which increases the risk of long-term health problems.

Abstract:
BACKGROUND: The coronavirus disease of 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).
While systemic inflammation and pulmonary complications can result in significant morbidity and mortality, cardiovascular complications may also occur.
OBJECTIVE: This brief report evaluates cardiovascular complications in the setting of COVID-19 infection.
DISCUSSION: The current COVID-19 pandemic has resulted in over one million infected worldwide and thousands of death.
The virus binds and enters through angiotensin-converting enzyme 2 (ACE2).
COVID-19 can result in systemic inflammation, multiorgan dysfunction, and critical illness.
The cardiovascular system is also affected, with complications including myocardial injury, myocarditis, acute myocardial infarction, heart failure, dysrhythmias, and venous thromboembolic events.
Current therapies for COVID-19 may interact with cardiovascular medications.
CONCLUSIONS: Emergency clinicians should be aware of these cardiovascular complications when evaluating and managing the patient with COVID-19.

Answer: {"verdict": "SUPPORT", "evidence": ["The cardiovascular system is also affected, with complications including myocardial injury, myocarditis, acute myocardial infarction, heart failure, dysrhythmias, and venous thromboembolic events.", "Current therapies for COVID-19 may interact with cardiovascular medications."]}


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: Potent neutralizing antibodies from covid-19 patients define multiple targets of antigen

Abstract:
The rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had a large impact on global health, travel, and economy.
Therefore, preventative and therapeutic measures are urgently needed.
Here, we isolated monoclonal antibodies from three convalescent coronavirus disease 2019 (COVID-19) patients using a SARS-CoV-2 stabilized prefusion spike protein.
These antibodies had low levels of somatic hypermutation and showed a strong enrichment in VH1-69, VH3-30-3, and VH1-24 gene usage.
A subset of the antibodies was able to potently inhibit authentic SARS-CoV-2 infection at a concentration as low as 0.007 micrograms per milliliter.
Competition and electron microscopy studies illustrate that the SARS-CoV-2 spike protein contains multiple distinct antigenic sites, including several receptor-binding domain (RBD) epitopes as well as non-RBD epitopes.
In addition to providing guidance for vaccine design, the antibodies described here are promising candidates for COVID-19 treatment and prevention.

Answer: {"verdict": "CONTRADICT", "evidence": ["In addition to providing guidance for vaccine design, the antibodies described here are promising candidates for COVID-19 treatment and prevention."]}


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: To help slow the spread and reduce your risk of COVID-19, stay at least 6 feet away from others. Keeping physical distance is important, even if you are not sick.

Abstract:
The Australian and New Zealand governments both initiated strict social distancing measures in response to the COVID-19 pandemic in late March.
It remains difficult to quantify the impact this had in reducing the spread of the virus.
Bayesian structural time series model provide a model to quantify the scenario in which these government-level interventions were not placed.
Our models predict these strict social distancing measures caused a 79% and 61% reduction in the daily cases of COVID-19 across Australia and New Zealand respectively.
This provides both evidence and impetus for governments considering similar measures in response to COVID-19 and other pandemics.

Answer: {"verdict": "SUPPORT", "evidence": ["Our models predict these strict social distancing measures caused a 79% and 61% reduction in the daily cases of COVID-19 across Australia and New Zealand respectively.", "This provides both evidence and impetus for governments considering similar measures in response to COVID-19 and other pandemics."]}


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 virus can stay on surfaces long enough to be a source of transmission

Abstract:
Objectives: To evaluate SARS-CoV-2 surface and air contamination during the peak of the COVID-19 pandemic in London.
Design: Prospective cross-sectional observational study.
Setting: An acute NHS healthcare provider.
Participants: All inpatient wards were fully occupied by patients with COVID-19 at the time of sampling.
Interventions: Air and surface samples were collected from a range of clinical areas and a public area of the hospital.
An active air sampler was used to collect three or four 1.0 m3 air samples in each area.
Surface samples were collected by swabbing approximately 25 cm2 of items in the immediate vicinity of each air sample.
SARS-CoV-2 was detected by RT-qPCR and viral culture using Vero E6 and Caco2 cells; additionally the limit of detection for culturing SARS-CoV-2 dried onto surfaces was determined.
Main outcome measures: SARS-CoV-2 detected by PCR or culture.
Results: Viral RNA was detected on 114/218 (52.3%) of surface and 14/31 (38.7%) air samples but no virus was cultured.
The proportion of surface samples contaminated with viral RNA varied by item sampled and by clinical area.
Viral RNA was detected on surfaces and in air in public areas of the hospital but was more likely to be found in areas immediately occupied by COVID-19 patients (67/105 (63.8%) in areas immediately occupied by COVID-19 patients vs. 29/64 (45.3%) in other areas (odds ratio 0.5, 95% confidence interval 0.2-0.9, p=0.025, Fishers exact test).
The PCR Ct value for all surface and air samples (>30) indicated a viral load that would not be culturable.
Conclusions: Our findings of extensive viral RNA contamination of surfaces and air across a range of acute healthcare settings in the absence of cultured virus underlines the potential risk from surface and air contamination in managing COVID-19, and the need for effective use of PPE, social distancing, and hand/surface hygiene.

Answer: {"verdict": "SUPPORT", "evidence": ["Conclusions: Our findings of extensive viral RNA contamination of surfaces and air across a range of acute healthcare settings in the absence of cultured virus underlines the potential risk from surface and air contamination in managing COVID-19, and the need for effective use of PPE, social distancing, and hand/surface hygiene."]}


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 new coronavirus can persist in the body for at least two weeks after symptoms of the disease clear up.

Abstract:
Recent studies have provided insights into the pathogenesis of coronavirus disease 2019 (COVID-19)1-4.
Yet, longitudinal immunological correlates of disease outcome remain unclear.
Here, we serially analysed immune responses in 113 COVID-19 patients with moderate (non-ICU) and severe (ICU) disease.
Immune profiling revealed an overall increase in innate cell lineages with a concomitant reduction in T cell number.
We identify an association between early, elevated cytokines and worse disease outcomes.
Following an early increase in cytokines, COVID-19 patients with moderate disease displayed a progressive reduction in type-1 (antiviral) and type-3 (antifungal) responses.
In contrast, patients with severe disease maintained these elevated responses throughout the course of disease.
Moreover, severe disease was accompanied by an increase in multiple type 2 (anti-helminths) effectors including, IL-5, IL-13, IgE and eosinophils.
Unsupervised clustering analysis of plasma and peripheral blood leukocyte data identified 4 immune signatures, representing (A) growth factors, (B) type-2/3 cytokines, (C) mixed type-1/2/3 cytokines, and (D) chemokines that correlated with three distinct disease trajectories of patients.
The immune profile of patients who recovered with moderate disease was enriched in tissue reparative growth factor signature (A), while the profile for those with worsened disease trajectory had elevated levels of all four signatures.
Thus, we identified development of a maladapted immune response profile associated with severe COVID-19 outcome and early immune signatures that correlate with divergent disease trajectories.

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: Detection of antibodies to the sars-cov-2 spike glycoprotein in both serum and saliva coulds detection of infection

Abstract:
BACKGROUND: Detecting antibody responses during and after SARS-CoV-2 infection is essential in determining the seroepidemiology of the virus and the potential role of antibody in disease.
Scalable, sensitive and specific serological assays are essential to this process.
The detection of antibody in hospitalized patients with severe disease has proven straightforward; detecting responses in subjects with mild disease and asymptomatic infections has proven less reliable.
We hypothesized that the suboptimal sensitivity of antibody assays and the compartmentalization of the antibody response may contribute to this effect.
METHODS: We systemically developed an ELISA assay, optimising different antigens and amplification steps, in serum and saliva from symptomatic and asymptomatic SARS-CoV-2-infected subjects.
RESULTS: Using trimeric spike glycoprotein, rather than nucleocapsid enabled detection of responses in individuals with low antibody responses.
IgG1 and IgG3 predominate to both antigens, but more antispike IgG1 than IgG3 was detectable.
All antigens were effective for detecting responses in hospitalized patients.
Anti-spike, but not nucleocapsid, IgG, IgA and IgM antibody responses were readily detectable in saliva from non-hospitalized symptomatic and asymptomatic individuals.
Antibody responses in saliva and serum were largely independent of each other and symptom reporting.
CONCLUSIONS.
Detecting antibody responses in both saliva and serum is optimal for determining virus exposure and understanding immune responses after SARS-CoV-2 infection.
FUNDING.
This work was funded by the University of Birmingham, the National Institute for Health Research (UK), the NIH National Institute for Allergy and Infectious Diseases, the Bill and Melinda Gates Foundation and the University of Southampton.

Answer: {"verdict": "CONTRADICT", "evidence": ["Anti-spike, but not nucleocapsid, IgG, IgA and IgM antibody responses were readily detectable in saliva from non-hospitalized symptomatic and asymptomatic individuals.", "Antibody responses in saliva and serum were largely independent of each other and symptom reporting."]}


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: If Fever Helps Fight Infection, Should I Avoid Fever-Reducing Drugs

Abstract:
OBJECTIVE: It was recently suggested that ibuprofen might increase the risk for severe and fatal coronavirus disease 2019 (COVID-19) and should therefore be avoided in this patient population.
We aimed to evaluate whether ibuprofen use in individuals with COVID-19 was associated with more severe disease, compared with individuals using paracetamol or no antipyretics.
METHODS: In a retrospective cohort study of patients with COVID-19 from Shamir Medical Centre, Israel, we monitored any use of ibuprofen from a week before diagnosis of COVID-19 throughout the disease.
Primary outcomes were mortality and the need for respiratory support, including oxygen administration and mechanical ventilation.
RESULTS: The study included 403 confirmed cases of COVID-19, with a median age of 45 years.
Of the entire cohort, 44 patients (11%) needed respiratory support and 12 (3%) died.
One hundred and seventy-nine (44%) patients had fever, with 32% using paracetamol and 22% using ibuprofen, for symptom-relief.
In the ibuprofen group, 3 (3.4%) patients died, whereas in the non-ibuprofen group, 9 (2.8%) patients died (p 0.95).
Nine (10.3%) patients from the ibuprofen group needed respiratory support, compared with 35 (11%) from the non-ibuprofen group (p 1).
When compared with exclusive paracetamol users, no differences were observed in mortality rates or the need for respiratory support among patients using ibuprofen.
CONCLUSIONS: In this cohort of COVID-19 patients, ibuprofen use was not associated with worse clinical outcomes, compared with paracetamol or no antipyretic.

Answer: {"verdict": "CONTRADICT", "evidence": ["When compared with exclusive paracetamol users, no differences were observed in mortality rates or the need for respiratory support among patients using ibuprofen.", "CONCLUSIONS: In this cohort of COVID-19 patients, ibuprofen use was not associated with worse clinical outcomes, compared with paracetamol or no antipyretic."]}


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: Hidden immune weakness found in gravely ill COVID-19 patients.

Abstract:
The rapid global spread of SARS-CoV-2 and resultant mortality and social disruption have highlighted the need to better understand coronavirus immunity to expedite vaccine development efforts.
Multiple candidate vaccines, designed to elicit protective neutralising antibodies targeting the viral spike glycoprotein, are rapidly advancing to clinical trial.
However, the immunogenic properties of the spike protein in humans are unresolved.
To address this, we undertook an in-depth characterisation of humoral and cellular immunity against SARS-CoV-2 spike in humans following mild to moderate SARS-CoV-2 infection.
We find serological antibody responses against spike are routinely elicited by infection and correlate with plasma neutralising activity and capacity to block ACE2/RBD interaction.
Expanded populations of spike-specific memory B cells and circulating T follicular helper cells (cTFH) were detected within convalescent donors, while responses to the receptor binding domain (RBD) constitute a minor fraction.
Using regression analysis, we find high plasma neutralisation activity was associated with increased spike-specific antibody, but notably also with the relative distribution of spike-specific cTFH subsets.
Thus both qualitative and quantitative features of B and T cell immunity to spike constitute informative biomarkers of the protective potential of novel SARS-CoV-2 vaccines.

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: Young people as diligent about Covid measures as older people

Abstract:
OBJECTIVES: To determine mortality rates among adults with critical illness from coronavirus disease 2019.
DESIGN: Observational cohort study of patients admitted from March 6, 2020, to April 17, 2020.
SETTING: Six coronavirus disease 2019 designated ICUs at three hospitals within an academic health center network in Atlanta, Georgia, United States.
PATIENTS: Adults greater than or equal to 18 years old with confirmed severe acute respiratory syndrome-CoV-2 disease who were admitted to an ICU during the study period.
INTERVENTIONS: None.
MEASUREMENTS AND MAIN RESULTS: Among 217 critically ill patients, mortality for those who required mechanical ventilation was 35.7% (59/165), with 4.8% of patients (8/165) still on the ventilator at the time of this report.
Overall mortality to date in this critically ill cohort is 30.9% (67/217) and 60.4% (131/217) patients have survived to hospital discharge.
Mortality was significantly associated with older age, lower body mass index, chronic renal disease, higher Sequential Organ Failure Assessment score, lower PaO2/FIO2 ratio, higher D-dimer, higher C-reactive protein, and receipt of mechanical ventilation, vasopressors, renal replacement therapy, or vasodilator therapy.
CONCLUSIONS: Despite multiple reports of mortality rates exceeding 50% among critically ill adults with coronavirus disease 2019, particularly among those requiring mechanical ventilation, our early experience indicates that many patients survive their critical illness.

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: headaches are rarely the sole symptom present in a coronavirus patient.

Abstract:
OBJECTIVE: The aim of this manuscript is to investigate transversally Ear Nose Throat (ENT) symptoms COVID-19 infection correlated and to study the neurotropism and neuroinvasiveness of the virus in the head-neck district through the investigation of the sense of smell, taste, tearing, salivation and hearing.
METHODS: A total of 50 patients with laboratory-confirmed COVID-19 infection were included in our study.
For each patient we evaluated the short version of the Questionnaire of Olfactory Disorders-Negative Statements (sQOD-NS), the Summated Xerostomia Inventory-Dutch Version (SXI-DV), The Standardized Patient Evaluation of Eye Dryness (SPEED), Schirmer test I, the Hearing Handicap Inventory For Adults (HHIA) and the Tinnitus Handicap Inventory (THI).
All the tests we carried out were performed during the active phase of the symptomatology from COVID-19 (Condition A) and 15 after SARS-COV-2 RT-PCR test negative (Condition B).
RESULTS: A total of 46 patients (92%) had olfactory dysfunction related to the infection.
The 70% of patients reported gustatory disorders.
Cough, fever, headache and asthenia were the most prevalent symptoms.
There was a statistically significant difference (p < 0,001) in sQOD-NS, SXI-DV, SPEED, Schirmer test, HHIA and THI between Condition A and Condition B. CONCLUSIONS: In our population there was an alteration of the sense of taste, of the sense of smell, dry eyes and of the oral cavity and an auditory discomfort, symptoms probably linked to the neurotropism of the virus.
Furthermore, anosmia, dysgeusia and xerostomia are early symptoms of COVID-19, which can be exploited for an early quarantine and a limitation of viral contagion.

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: Because some of the symptoms of flu and COVID-19 are similar, it may be hard to tell the difference between them based on symptoms alone

Abstract:
Coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) has turned out to be a formidable pandemic.
Upcoming evidence from confirmed cases of COVID-19 suggests an anticipated incursion of patients with neurological manifestations in the weeks to come.
An expression of the angiotensin-converting enzyme 2 (ACE 2), the cellular receptor for SARS-CoV-2 over the glial cells and neurons have made the brain a potential target.
Neurotoxicity may occur as a result of direct, indirect and post-infectious complications.
Attention to neurological deficits in COVID-19 is fundamental to ensure appropriate, timely, beneficial management of the affected patients.
Most common neurological manifestations seen include dizziness, headache, impaired consciousness, acute cerebrovascular disease, ataxia, and seizures.
Anosmia and ageusia have recently been hinted as significant early symptoms in COVID-19.
As cases with neurological deficits in COVID-19 emerge, the overall prognosis is yet unknown.

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: Hydroxychloroquine safety outcome within approved therapeutic protocol of covid-19 outpatients in saudi arabia

Abstract:
Background: Healthcare systems globally has been challenged following the COVID-19 pandemic, since late 2019.
Multiple approaches and strategies have been performed to relieve the pressure and support existing healthcare systems.
The Saudi Arabian Ministry of Health (MOH) launched an initiative to support the National Healthcare System.
Since the 5th of June 2020, 238 outpatient fever clinics were established across Saudi Arabia.
Methods: A cross-sectional study included 2,733 eligible patients subjected to MOH treatment protocol (hydroxychloroquine and zinc) and revisited the clinics within 3-7 days after treatment initiation.
This study aimed to assess the safety outcome and reported adverse events from hydroxychloroquine use among suspected COVID-19 patients.
The data was collected through an electronic link and cross-checked with that of the national database (Health Electronic Surveillance Network, HESN) and reports from the MOH Morbidity and Mortality (M&M) Committee.
Results: Majority of the cases were males (70.4%).
Upon reassessing the studied participants within 3-7 days, 240 patients (8.8%) discontinued the treatment protocol because of the development of side effects (4.1%) and for non-clinical reasons in the remaining (4.7%).
Medication side effects overall were reported among (6.7%) of all studied participants, including mainly cardiovascular adverse events (2.5%), followed by gastrointestinal (GI) symptoms (2.4%).
No Intensive Care Unit (ICU) admission or death were reported among these patients.
Conclusion: In our study, results show that the use of hydroxychloroquine for COVID-19 patients in mild to moderate cases in an outpatient setting, within the protocol recommendation and inclusion/exclusion criteria, is safe, highly tolerable, and with minimum side effects.

Answer: {"verdict": "CONTRADICT", "evidence": ["Conclusion: In our study, results show that the use of hydroxychloroquine for COVID-19 patients in mild to moderate cases in an outpatient setting, within the protocol recommendation and inclusion/exclusion criteria, is safe, highly tolerable, and with minimum side effects."]}


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: Green tea: Green tea is an excellent source of antiviral and anti-inflammatory catechins, notably, one called epigallocatechin gallate, or EGCG.

Abstract:
Coronavirus disease 2019 (COVID-19) is a viral respiratory disease which caused global health emergency and announced as pandemic disease by World Health Organization.
Lack of specific drug molecules or treatment strategy against this disease makes it more devastating.
Thus, there is an urgent need of effective drug molecules to fight against COVID-19.
The main protease (Mpro) of SARS CoV-2, a key component of this viral replication, is considered as a prime target for anti-COVID-19 drug development.
In order to find potent Mpro inhibitors, we have selected eight polyphenols from green tea, as these are already known to exert antiviral activity against many RNA viruses.
We have elucidated the binding affinities and binding modes between these polyphenols including a well-known Mpro inhibitor N3 (having binding affinity -7.0 kcal/mol) and Mpro using molecular docking studies.
All eight polyphenols exhibit good binding affinity toward Mpro (-7.1 to -9.0 kcal/mol).
However, only three polyphenols (epigallocatechin gallate, epicatechingallate and gallocatechin-3-gallate) interact strongly with one or both catalytic residues (His41 and Cys145) of Mpro.
Molecular dynamics simulations (100 ns) on these three Mpro-polyphenol systems further reveal that these complexes are highly stable, experience less conformational fluctuations and share similar degree of compactness.
Estimation of total number of intermolecular H-bond and MM-GBSA analysis affirm the stability of these three Mpro-polyphenol complexes.
Pharmacokinetic analysis additionally suggested that these polyphenols possess favorable drug-likeness characteristics.
Altogether, our study shows that these three polyphenols can be used as potential inhibitors against SARS CoV-2 Mpro and are promising drug candidates for COVID-19 treatment.
Communicated by Ramaswamy H. Sarma.

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: Circulating mitochondrial dna is an early indicator of severe illness and mortality from covid-19

Abstract:
Mitochondrial DNA (MT-DNA) are intrinsically inflammatory nucleic acids released by damaged solid organs.
Whether the appearance of cell-free MT-DNA is linked to poor COVID-19 outcomes remains undetermined.
Here, we quantified circulating MT-DNA in prospectively collected, cell-free plasma samples from 97 subjects with COVID-19 at the time of hospital presentation.
Circulating MT-DNA were sharply elevated in patients who eventually died, required ICU admission or intubation.
Multivariate regression analysis revealed that high circulating MT-DNA levels is an independent risk factor for all of these outcomes after adjusting for age, sex and comorbidities.
Additionally, we found that circulating MT-DNA has a similar or superior area-under-the curve when compared to clinically established measures of systemic inflammation, as well as emerging markers currently of interest as investigational targets for COVID-19 therapy.
These results show that high circulating MT-DNA levels is a potential indicator for poor COVID-19 outcomes.

Answer: {"verdict": "SUPPORT", "evidence": ["Multivariate regression analysis revealed that high circulating MT-DNA levels is an independent risk factor for all of these outcomes after adjusting for age, sex and comorbidities.", "These results show that high circulating MT-DNA levels is a potential indicator for poor COVID-19 outcomes."]}


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 experts are remotely advocating for people to take up smoking to prevent COVID-19, but some researchers have theorized nicotine may be playing some role in keeping the virus at bay

Abstract:
Introduction Epidemiological and laboratory research seems to suggest that smoking and perhaps nicotine alone could reduce the severity of COVID-19.
Likewise, there is some evidence that inhaled corticosteroids could also reduce its severity, opening the possibility that nicotine and inhaled steroids could be used as treatments.
Methods In this prospective cohort study, we will link English general practice records from the QResearch database to Public Health England's database of SARS-CoV-2 positive tests, Hospital Episode Statistics, admission to intensive care units, and death from COVID-19 to identify our outcomes: hospitalisation, ICU admission, and death due to COVID.
Using Cox regression, we will perform sequential adjustment for potential confounders identified by separate directed acyclic graphs to: 1.
Assess the association between smoking and COVID-19 disease severity, and how that changes on adjustment for smoking-related comorbidity.
2. More closely characterise the association between smoking and severe COVID-19 disease by assessing whether the association is modified by age (as a proxy of length of smoking), gender, ethnic group, and whether people have asthma or COPD.
3. Assess for evidence of a dose-response relation between smoking intensity and disease severity, which would help create a case for causality.
4.
Examine the association between former smokers who are using NRT or are vaping and disease severity.
5. Examine whether pre-existing respiratory disease is associated with severe COVID-19 infection.
6. Assess whether the association between chronic obstructive pulmonary disease (COPD) and asthma and COVID-19 disease severity is modified by age, gender, ethnicity, and smoking status.
7. Assess whether the use of inhaled corticosteroids is associated with severity of COVID-19 disease.
8. To assess whether the association between use of inhaled corticosteroids and severity of COVID-19 disease is modified by the number of other airways medications used (as a proxy for severity of condition) and whether people have asthma or COPD.
Conclusions This representative population sample will, to our knowledge, present the first comprehensive examination of the association between smoking, nicotine use without smoking, respiratory disease, and severity of COVID-19.
We will undertake several sensitivity analyses to examine the potential for bias in these associations.

Answer: {"verdict": "SUPPORT", "evidence": ["Introduction Epidemiological and laboratory research seems to suggest that smoking and perhaps nicotine alone could reduce the severity of COVID-19."]}