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: Many mammals around the world could have a role in spreading the disease, including dogs and cats.

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

Answer: {"verdict": "CONTRADICT", "evidence": ["Notification of presumptive positive animal test results triggered a One Health* investigation by state and federal partners, who determined that no further transmission events to other animals or persons had occurred.", "Although there is currently no evidence that animals play a substantial role in spreading COVID-19, CDC advises persons with suspected or confirmed COVID-19 to restrict contact with animals during their illness and to monitor any animals with confirmed SARS-CoV-2 infection and separate them from other persons and animals at home (1)."]}


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

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

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

Claim: It does not make a lot of sense that if somebody is otherwise healthy and young and they have hypertension alone, that they should be at increased risk

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

Answer: {"verdict": "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: If the person is asymptomatic but was tested after having close contact with someone with SARS-CoV-2 infection or as part of a response to an outbreak (e.g., facility has a resident with nursing-home onset COVID-19 or a HCP with COVID-19), then they should also be considered to have SARS-CoV-2 infection and managed as described above.

Abstract:
Abstract Asymptomatic but infectious people have been reported in many infectious diseases.
Asymptomatic and pre-symptomatic carriers would be a hidden reservoir of COVID-19.
Aim This review identifies primary empirical evidence about the ability of asymptomatic carriers to infect others with COVID-19 pandemic and reflects on the implications for control measures.
Methods A systematic review is followed by a narrative report and commentary inclusion criteria were: studies reporting primary data on asymptomatic or pre-symptomatic patients, who were considered to have passed on COVID-19 infection; and published in indexed journals or in peer review between January 1 and March 31, 2020.
Results Nine articles reported on 83 asymptomatic or pre-symptomatic persons.
Conclusions The evidence confirms COVID-19 transmission from people who were asymptomatic at the time.
A series of implications for health service response are laid out.
Keywords: Covid-19, Asymptomatic, Pre-symptomatic, Public Health

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


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

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

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

Claim: Can COVID-19 be spread from pets to people or other pets? According to the latest information from the CDC , the risk of animals spreading COVID-19 to people is very low. However, because all animals can carry germs that can make people sick, it's always a good idea to practice healthy habits around pets and other animals.

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

Answer: {"verdict": "SUPPORT", "evidence": ["Coronavirus disease-19 (COVID-19) caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is now a pandemic threat.", "This virus is supposed to be spread by human to human transmission.", "Experimental data showed ferrets and cats are highly susceptible to SARS-CoV-2 as infected by virus inoculation and can transmit the virus directly or indirectly by droplets or airborne routes."]}


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: Thrombotic microvascular injury is also mediated by thrombotic microangiopathy despite systemic complement activation in covid-19 patients

Abstract:
Hypoxemia and coagulopathy are common in severe symptomatic patients of coronavirus disease 2019 (COVID-19).
Histological evidence shows implication of complement activation and lung injury.
We research sign of complement activation and presence of thrombotic microangiopathy in 8 severe patients.
Six of them presented moderate elevation of final pathway of complement / sC5b-9 (median value : 350 ng/mL [IQR : 300,5-514,95 ng/mL]).
Two patients have been autopsied and presence of thrombotic microvascular injury have been found.
Interestingly, none the 8 patients had signs of mechanical hemolytic anemia (median value of hemoglobin : 10,5 gr/dL[IQR : 8,1-1,9], median value of haptoglobuline 4,49 [IQR 3,55-4,66], none of the patients has schistocyte) and thrombocytopenia (median value: 348000/mL [IQR : 266 000-401 000).
Finally, all 8 patients had elevated d-dimer (median value : 2226 microgr/l [IQR : 1493-2362]) and soluble fibrin monomer complex (median value : 8.5 mg/mL, IQR[ <6-10.6]).
In summary, this study show moderate activation of complement and coagulation with presence of thrombotic microvascular injury in patients with severe COVID-19 without evidence of systemic thrombotic microangiopathy.

Answer: {"verdict": "CONTRADICT", "evidence": ["In summary, this study show moderate activation of complement and coagulation with presence of thrombotic microvascular injury in patients with severe COVID-19 without evidence of systemic thrombotic microangiopathy."]}


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 D might help protect against becoming infected with, and developing serious symptoms of, COVID-19

Abstract:
Importance: Vitamin D treatment has been found to decrease incidence of viral respiratory tract infection, especially in vitamin D deficiency.
It is unknown whether COVID-19 incidence is associated with vitamin D deficiency and treatment.
Objective: To examine whether vitamin D deficiency and treatment are associated with testing positive for COVID-19.
Design: Retrospective cohort study Setting: University of Chicago Medicine Participants: Patients tested for COVID-19 from 3/3/2020-4/10/2020.
Vitamin D deficiency was defined by the most recent 25-hydroxycholecalciferol <20ng/ml or 1,25-dihydroxycholecalciferol <18pg/ml within 1 year before COVID-19 testing.
Treatment was defined by the most recent vitamin D type and dose, and treatment changes between the time of the most recent vitamin D level and time of COVID-19 testing.
Vitamin D deficiency and treatment changes were combined to categorize vitamin D status at the time of COVID-19 testing as likely deficient(last-level-deficient/treatment-not-increased), likely sufficient(last-level-not-deficient/treatment-not-decreased), or uncertain deficiency(last-level-deficient/treatment-increased or last-level-not-deficient/treatment-decreased).
Main Outcomes and Measures: The main outcome was testing positive for COVID-19.
Multivariable analysis tested whether the most recent vitamin D level and treatment changes after that level were associated with testing positive for COVID-19 controlling for demographic and comorbidity indicators.
Bivariate analyses of associations of treatment with vitamin D deficiency and COVID-19 were performed.
Results: Among 4,314 patients tested for COVID-19, 499 had a vitamin D level in the year before testing.
Vitamin D status at the time of COVID-19 testing was categorized as likely deficient for 127(25%) patients, likely sufficient for 291(58%) patients, and uncertain for 81(16%) patients.
In multivariate analysis, testing positive for COVID-19 was associated with increasing age(RR(age<50)=1.05,p<0.021;RR(age[≥]50)=1.02,p<0.064)), non-white race(RR=2.54,p<0.01) and being likely vitamin D deficient (deficient/treatment-not-increased:RR=1.77,p<0.02) as compared to likely vitamin D sufficient(not-deficient/treatment-not-decreased), with predicted COVID-19 rates in the vitamin D deficient group of 21.6%(95%CI[14.0%-29.2%] ) versus 12.2%(95%CI[8.9%-15.4%]) in the vitamin D sufficient group.
Vitamin D deficiency declined with increasing vitamin D dose, especially of vitamin D3.
Vitamin D dose was not significantly associated with testing positive for COVID-19.
Conclusions and Relevance: Vitamin D deficiency that is not sufficiently treated is associated with COVID-19 risk.
Testing and treatment for vitamin D deficiency to address COVID-19 warrant aggressive pursuit and study.

Answer: {"verdict": "SUPPORT", "evidence": ["Conclusions and Relevance: Vitamin D deficiency that is not sufficiently treated is associated with COVID-19 risk."]}


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: Avoid medications to lower fever if sick with the new coronavirus

Abstract:
Concern about the appropriate role of nonsteroidal anti-inflammatory drugs (NSAIDs) in COVID-19 speculate that NSAIDs, in particular ibuprofen, may upregulate the entry point for the virus, the angiotensin-converting enzyme (ACE) 2 receptors and increase susceptibility to the virus or worsen symptoms in existing disease.
Adverse outcomes with COVID-19 have been linked to cytokine storm but the most effective way to address exaggerated inflammatory response is complex and unclear.
The Expert Working Group on the Commission of Human Medicines in the UK and other organizations have stated that there is insufficient evidence to establish a link between ibuprofen and susceptibility to or exacerbation of COVID-19.
NSAID use must also be categorized by whether the drugs are relatively low-dose over-the-counter oral products taken occasionally versus higher-dose or parenteral NSAIDs.
Even if evidence emerged arguing for or against NSAIDs in this setting, it is unclear if this evidence would apply to all NSAIDs at all doses in all dosing regimens.
Paracetamol (acetaminophen) has been proposed as an alternative to NSAIDs but there are issues with liver toxicity at high doses.
There are clearly COVID-19 cases where NSAIDs should not be used, but there is no strong evidence that NSAIDs must be avoided in all patients with COVID-19; clinicians must weigh these choices on an individual basis.

Answer: {"verdict": "CONTRADICT", "evidence": ["The Expert Working Group on the Commission of Human Medicines in the UK and other organizations have stated that there is insufficient evidence to establish a link between ibuprofen and susceptibility to or exacerbation of COVID-19.", "There are clearly COVID-19 cases where NSAIDs should not be used, but there is no strong evidence that NSAIDs must be avoided in all patients with COVID-19; clinicians must weigh these choices on an individual basis."]}


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: So, COVID is killed by heat. That is why our bodies create fever to fight it off. When you take Tylenol or advil it takes away your fever and allows COVID its ideal environment. If you get COVID allow your fever to remain as long as it is not over 103-104 this is your body fighting the virus.

Abstract:
Fever has been reported as a common symptom occurring in COVID-19 illness.
Over the counter antipyretics such as ibuprofen and acetaminophen are often taken by individuals to reduce the discomfort of fever.
Recently, the safety of ibuprofen in COVID-19 patients has been questioned due to anecdotal reports of worsening symptoms in previously healthy young adults.
Studies show that ibuprofen demonstrates superior efficacy in fever reduction compared to acetaminophen.
As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness.

Answer: {"verdict": "CONTRADICT", "evidence": ["As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness."]}


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 reduce the spread of the virus: try to stay at least 2 metres (3 steps) away from anyone you do not live with (or anyone not in your support bubble); wash your hands with soap and water often - do this for at least 20 seconds; use hand sanitiser gel if soap and water are not available; wash your hands as soon as you get home; cover your mouth and nose with a tissue or your sleeve (not your hands) when you cough or sneeze; put used tissues in the bin immediately and wash your hands afterwards

Abstract:
Background: The Greek authorities implemented the strong social distancing measures within the first few weeks after the first confirmed case of the virus to curtail the COVID-19 growth rate.
Objectives: To estimate the effect of the two-stage strong social distancing measures, the closure of all non-essential shopping centers and businesses on March 16 and the shelter in place orders (SIPOs) on March 23 on the COVID-19 growth rate in Greece Methods: We obtained data on COVID-19 cases in Greece from February 26th through May 4th from publicly available sources.
An interrupted time-series regression analysis was used to estimate the effect of the measures on the exponential growth of confirmed COVID-19 cases, controlling for the number of daily testing, and weekly fixed-effects.
Results: The growth rate of the COVID-19 cases in the pre-policies implementation period was positive as expected (p=0.003).
Based on the estimates of the interrupted time-series, our results indicate that the SIPO on March 23 significantly slowed the growth rate of COVID-19 in Greece (p=0.04).
However, we did not find evidence on the effectiveness of standalone and partial measures such as the non-essential business closures implemented on March 16 on the COVID-19 spread reduction.
Discussion: The combined social distancing measures implemented by the Greek authorities within the first few weeks after the first confirmed case of the virus reduced the COVID-19 growth rate.
These findings provide evidence and highlight the effectiveness of these measures to flatten the curve and to slow the spread of the virus.

Answer: {"verdict": "SUPPORT", "evidence": ["Discussion: The combined social distancing measures implemented by the Greek authorities within the first few weeks after the first confirmed case of the virus reduced the COVID-19 growth rate."]}


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: Iga dominates the full neutralizing antibody response to sars-cov-2

Abstract:
Humoral immune responses are typically characterized by primary IgM antibody responses followed by secondary antibody responses associated with immune memory and comprised of of IgG, IgA and IgE. Here we measured acute humoral responses to SARS-CoV-2, including the frequency of antibody-secreting cells and the presence of SARS-CoV-2-specific neutralizing antibodies in the serum, saliva and broncho-alveolar fluid of 159 patients with COVID-19.
Early SARS-CoV-2-specific humoral responses were dominated by IgA antibodies.
Peripheral expansion of IgA plasmablasts with mucosal-homing potential was detected shortly after the onset of symptoms and peaked during the third week of the disease.
The virus-specific antibody responses included IgG, IgM and IgA, but IgA contributed to virus neutralization to a greater extent compared with IgG. Specific IgA serum concentrations decreased notably one month after the onset of symptoms, but neutralizing IgA remained detectable in saliva for a longer time (days 49 to 73 post symptoms).
These results represent a critical observation given the emerging information as to the types of antibodies associated with optimal protection against re-infection, and whether vaccine regimens should consider targeting a potent but potentially short-lived IgA response.

Answer: {"verdict": "CONTRADICT", "evidence": ["Early SARS-CoV-2-specific humoral responses were dominated by IgA antibodies."]}


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: camostat mesylate cure coronavirus.

Abstract:
The outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has posed the world at a pandemic risk.
Coronavirus-19 disease (COVID-19) is an infectious disease caused by SARS-CoV-2, which causes pneumonia, requires intensive care unit hospitalization in about 10% of cases and can lead to a fatal outcome.
Several efforts are currently made to find a treatment for COVID-19 patients.
So far, several anti-viral and immunosuppressive or immunomodulating drugs have demonstrated some efficacy on COVID-19 both in vitro and in animal models as well as in cases series.
In COVID-19 patients a pro-inflammatory status with high levels of interleukin (IL)-1B, IL-1 receptor (R)A and tumor necrosis factor (TNF)-α has been demonstrated.
Moreover, high levels of IL-6 and TNF-α have been observed in patients requiring intensive-care-unit hospitalization.
This provided rationale for the use of anti-rheumatic drugs as potential treatments for this severe viral infection.
Other agents, such as hydroxychloroquine and chloroquine might have a direct anti-viral effect.
The anti-viral aspect of immunosuppressants towards a variety of viruses has been known since long time and it is herein discussed in the view of searching for a potential treatment for SARS-CoV-2 infection.

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


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

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

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

Claim: Dogs can test positive for the virus.

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

Answer: {"verdict": "SUPPORT", "evidence": ["Notification of presumptive positive animal test results triggered a One Health* investigation by state and federal partners, who determined that no further transmission events to other animals or persons had occurred."]}


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: Sequence mapping of viral mutations that escape antibodies used to treat covid-19

Abstract:
Antibodies are becoming a frontline therapy for SARS-CoV-2, but the risk of viral evolutionary escape remains unclear.
Here we map how all mutations to SARS-CoV-2’s receptor-binding domain (RBD) affect binding by the antibodies in Regeneron’s REGN-COV2 cocktail and Eli Lilly’s LY-CoV016.
These complete maps uncover a single amino-acid mutation that fully escapes the REGN-COV2 cocktail, which consists of two antibodies targeting distinct structural epitopes.
The maps also identify viral mutations that are selected in a persistently infected patient treated with REGN-COV2, as well as in lab viral escape selections.
Finally, the maps reveal that mutations escaping each individual antibody are already present in circulating SARS-CoV-2 strains.
Overall, these complete escape maps enable immediate interpretation of the consequences of mutations observed during viral surveillance.

Answer: {"verdict": "CONTRADICT", "evidence": ["Finally, the maps reveal that mutations escaping each individual antibody are already present in circulating SARS-CoV-2 strains."]}


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

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

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

Claim: People with weakened immune systems are at higher risk of getting severely sick from SARS-CoV-2, the virus that causes COVID-19.

Abstract:
Several related human coronaviruses (HCoVs) are endemic in the human population, causing mild respiratory infections1.
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the etiologic agent of Coronavirus disease 2019 (COVID-19), is a recent zoonotic infection that has quickly reached pandemic spread2,3.
Zoonotic introduction of novel coronaviruses is thought to occur in the absence of pre-existing immunity in the target human population.
Using diverse assays for detection of antibodies reactive with the SARS-CoV-2 Spike (S) glycoprotein, we demonstrate the presence of pre-existing immunity in uninfected and unexposed humans to the new coronavirus.
SARS-CoV-2 S-reactive antibodies, exclusively of the IgG class, were readily detectable by a sensitive flow cytometry-based method in SARS-CoV-2-uninfected individuals with recent HCoV infection and targeted the S2 subunit.
In contrast, SARS-CoV-2 infection induced higher titres of SARS-CoV-2 S-reactive IgG antibodies, as well as concomitant IgM and IgA antibodies throughout the observation period of 6 weeks since symptoms onset.
HCoV patient sera also variably reacted with SARS-CoV-2 S and nucleocapsid (N), but not with the S1 subunit or the receptor binding domain (RBD) of S on standard enzyme immunoassays.
Notably, HCoV patient sera exhibited specific neutralising activity against SARS-CoV-2 S pseudotypes, according to levels of SARS-CoV-2 S-binding IgG and with efficiencies comparable to those of COVID-19 patient sera.
Distinguishing pre-existing and de novo antibody responses to SARS-CoV-2 will be critical for serology, seroprevalence and vaccine studies, as well as for our understanding of susceptibility to and natural course of SARS-CoV-2 infection.

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: Only an N95 mask will help me from getting covid-19.

Abstract:
In the context of Coronavirus Disease (2019) (COVID-19) cases globally, there is a lack of consensus across cultures on whether wearing face masks is an effective physical intervention against disease transmission.
This study 1) illustrates transmission routes of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2); 2) addresses controversies surrounding the mask from perspectives of attitude, effectiveness, and necessity of wearing the mask with evidence that the use of mask would effectively interrupt the transmission of infectious diseases in both hospital settings and community settings; and 3) provides suggestion that the public should wear the mask during COVID-19 pandemic according to local context.
To achieve this goal, government should establish a risk adjusted strategy of mask use to scientifically publicize the use of masks, guarantee sufficient supply of masks, and cooperate for reducing health resources inequities.

Answer: {"verdict": "CONTRADICT", "evidence": ["This study 1) illustrates transmission routes of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2); 2) addresses controversies surrounding the mask from perspectives of attitude, effectiveness, and necessity of wearing the mask with evidence that the use of mask would effectively interrupt the transmission of infectious diseases in both hospital settings and community settings; and 3) provides suggestion that the public should wear the mask during COVID-19 pandemic according to local context."]}


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: Sars-cov1 frequent mask use in public venues, frequent hand washing, and disinfecting the living quarters were less protective factors

Abstract:
We analyzed information obtained from 1,192 patients with probable severe acute respiratory syndrome (SARS) reported in Hong Kong.
Among them, 26.6% were hospital workers, 16.1% were household members of SARS patients and had probable secondary infections, 14.3% were Amoy Garden residents, 4.9% were inpatients, and 20.1% were contacts of SARS patients who were not family members.
The remaining 347 case-patients (29.1%) did not have “known” sources of infection.
Excluding those <16 years of age, 330 patients with cases from “undefined” sources were used in a 1:2 matched case-control study.
Multivariate analysis of this case-control study showed that having visited mainland China, hospitals, or the Amoy Gardens were risk factors (odds ratio [OR] 1.95 to 7.63).
In addition, frequent mask use in public venues, frequent hand washing, and disinfecting the living quarters were significant protective factors (OR 0.36 to 0.58).
In Hong Kong, therefore, community-acquired infection did not make up most transmissions, and public health measures have contributed substantially to the control of the SARS epidemic.

Answer: {"verdict": "CONTRADICT", "evidence": ["In addition, frequent mask use in public venues, frequent hand washing, and disinfecting the living quarters were significant protective factors (OR 0.36 to 0.58)."]}


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

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

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

Claim: high doses of vitamins and natural remedies can stave off COVID-19 — but evidence to support these claims is lacking.

Abstract:
The new Corona-virus, recently called the severe acute respiratory syndrome Coronavirus (SARS-CoV-2) appears for the first time in China and more precisely in Wuhan (December 2019).
This disease can be fatal.
Seniors, and people with other medical conditions (diabetes, heart disease ), may be more vulnerable and become seriously ill.
This is why research into drugs to treat this infection remains essential in several research laboratories.
Natural herbal remedies have long been the main, if not the only, remedy in the oral tradition for treating illnesses.
Modern medicine has known its success thanks to traditional medicine, the effectiveness of which derives from medicinal plants.
The objective of this study is to determine if the components of natural origin have an anti-viral effect and which can prevent humans from infection by this coronavirus using the most reliable method is molecular docking, which used to find the interaction between studied molecules and the protein, in our case we based on the inhibitor of Coronavirus (nCoV-2019) main protease.
The results of molecular docking showed that among 67 molecules of natural origin, three molecules (Crocin, Digitoxigenin, and ß-Eudesmol) are proposed as inhibitors against the coronavirus based on the energy types of interaction between these molecules and studied protein.
[Formula: see text]Communicated by Ramaswamy H. SarmaHighlightsDetermine natural compounds that can have an anti-viral effect and which can prevent humans from infection by this coronavirus;Molecular docking to find interaction between the molecules studied and the receptor of COVID-19;The synthesis of these molecules and the evaluation of their in vitro activity against SARS-Cov-2 could be interesting.

Answer: {"verdict": "SUPPORT", "evidence": ["Natural herbal remedies have long been the main, if not the only, remedy in the oral tradition for treating illnesses."]}


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

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

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

Claim: Vitamins and Minerals Help Fight Coronavirus

Abstract:
OBJECTIVE Coronavirus disease 2019 (COVID-19) is a fatal and fast-spreading viral infection.
To date, the number of COVID-19 patients worldwide has crossed over six million with over three hundred and seventy thousand deaths (according to the data from World Health Organization; updated on 2 June 2020).
Although COVID-19 can be rapidly diagnosed, efficient clinical treatment of COVID-19 remains unavailable, resulting in high fatality.
Some clinical trials have identified vitamin C (VC) as a potent compound pneumonia management.
In addition, glycyrrhizic acid (GA) is clinically as an anti-inflammatory medicine against pneumonia-induced inflammatory stress.
We hypothesized that the combination of VC and GA is a potential option for treating COVID-19.
METHODS The aim of this study was to determine pharmacological targets and molecular mechanisms of VC + GA treatment for COVID-19, using bioinformational network pharmacology.
RESULTS We uncovered optimal targets, biological processes and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of VC + GA against COVID-19.
Our findings suggested that combinatorial VC and GA treatment for COVID-19 was associated with elevation of immunity and suppression of inflammatory stress, including activation of the T cell receptor signaling pathway, regulation of Fc gamma R-mediated phagocytosis, ErbB signaling pathway and vascular endothelial growth factor signaling pathway.
We also identified 17 core targets of VC + GA, which suggest as antimicrobial function.
CONCLUSIONS For the first time, our study uncovered the pharmacological mechanism underlying combined VC and GA treatment for COVID-19.
These results should benefit efforts to address the most pressing problem currently facing the world.

Answer: {"verdict": "CONTRADICT", "evidence": ["Although COVID-19 can be rapidly diagnosed, efficient clinical treatment of COVID-19 remains unavailable, resulting in high fatality."]}


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 Weather Network - Wildfire smoke could worsen COVID-19

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": "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: An ultra-potent synthetic nanobody neutralizes sars-cov-2 by locking light into an inactive conformation

Abstract:
Without an effective prophylactic solution, infections from SARS-CoV-2 continue to rise worldwide with devastating health and economic costs.
SARS-CoV-2 gains entry into host cells via an interaction between its Spike protein and the host cell receptor angiotensin converting enzyme 2 (ACE2).
Disruption of this interaction confers potent neutralization of viral entry, providing an avenue for vaccine design and for therapeutic antibodies.
Here, we develop single-domain antibodies (nanobodies) that potently disrupt the interaction between the SARS-CoV-2 Spike and ACE2.
By screening a yeast surface-displayed library of synthetic nanobody sequences, we identified a panel of nanobodies that bind to multiple epitopes on Spike and block ACE2 interaction via two distinct mechanisms.
Cryogenic electron microscopy (cryo-EM) revealed that one exceptionally stable nanobody, Nb6, binds Spike in a fully inactive conformation with its receptor binding domains (RBDs) locked into their inaccessible down-state, incapable of binding ACE2.
Affinity maturation and structure-guided design of multivalency yielded a trivalent nanobody, mNb6-tri, with femtomolar affinity for SARS-CoV-2 Spike and picomolar neutralization of SARS-CoV-2 infection.
mNb6-tri retains stability and function after aerosolization, lyophilization, and heat treatment.
These properties may enable aerosol-mediated delivery of this potent neutralizer directly to the airway epithelia, promising to yield a widely deployable, patient-friendly prophylactic and/or early infection therapeutic agent to stem the worst pandemic in a century.

Answer: {"verdict": "CONTRADICT", "evidence": ["Cryogenic electron microscopy (cryo-EM) revealed that one exceptionally stable nanobody, Nb6, binds Spike in a fully inactive conformation with its receptor binding domains (RBDs) locked into their inaccessible down-state, incapable of binding ACE2."]}


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: On-cov2 antibody cocktail prevents and treats sars-cov-2 infection in rhesus macaques and hamsters

Abstract:
An urgent global quest for effective therapies to prevent and treat COVID-19 disease is ongoing.
We previously described REGN-COV2, a cocktail of two potent neutralizing antibodies (REGN10987+REGN10933) targeting non-overlapping epitopes on the SARS-CoV-2 spike protein.
In this report, we evaluate the in vivo efficacy of this antibody cocktail in both rhesus macaques and golden hamsters and demonstrate that REGN-COV-2 can greatly reduce virus load in lower and upper airway and decrease virus induced pathological sequalae when administered prophylactically or therapeutically.
Our results provide evidence of the therapeutic potential of this antibody cocktail.

Answer: {"verdict": "CONTRADICT", "evidence": ["We previously described REGN-COV2, a cocktail of two potent neutralizing antibodies (REGN10987+REGN10933) targeting non-overlapping epitopes on the SARS-CoV-2 spike protein.", "In this report, we evaluate the in vivo efficacy of this antibody cocktail in both rhesus macaques and golden hamsters and demonstrate that REGN-COV-2 can greatly reduce virus load in lower and upper airway and decrease virus induced pathological sequalae when administered prophylactically or therapeutically.", "Our results provide evidence of the therapeutic potential of this antibody cocktail."]}


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 spreads mainly through small airborne droplets when an infected person coughs or sneezes.

Abstract:
The coronavirus disease (COVID-19) affecting across the globe.
The government of different countries has adopted various policies to contain this epidemic and the most common were social distancing and lockdown.
We use a simple log-linear model with intercept and trend break to evaluate whether the measures are effective preventing/slowing down the spread of the disease in Turkey.
We estimate the model parameters from the Johns Hopkins University (2020) epidemic data between 15th March and 16th April 2020.
Our analysis revealed that the measures can slow down the outbreak.
We can reduce the epidemic size and prolong the time to arrive at the epidemic peak by seriously following the measures suggested by the authorities.

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: 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:
Importance.
Covid-19 infection has major international health and economic impacts and risk factors for infection are not completely understood.
Cannabis smoking is linked with poor respiratory health, immunosuppression and multiple contaminants.
Potential synergism between the two epidemics would represent a major public health convergence.
Cigarettes were implicated with disease severity in Wuhan, China.
Objective.
Is cannabis use epidemiologically associated with coronavirus incidence rate (CVIR)?
Design.
Cross-sectional state-based multivariable study.
Setting.
USA.
Primary and Secondary Outcome Measures.
CVIR.
Multivariable-adjusted geospatially-weighted regression models.
As the American cannabis epidemic is characterized by a recent doubling of daily cannabis use it was considered important to characterize the contribution of high intensity use.
Results.
Significant associations of daily cannabis use quintile with CVIR were identified with the highest quintile having a prevalence ratio 5.11 (95%C.I. 4.90-5.33), an attributable fraction in the exposed (AFE) 80.45% (79.61-81.25%) and an attributable fraction in the population of 77.80% (76.88-78.68%) with Chi-squared-for-trend (14,782, df=4) significant at P<10-500.
Similarly when cannabis legalization was considered decriminalization was associated with an elevated CVIR prevalence ratio 4.51 (95%C.I. 4.45-4.58), AFE 77.84% (77.50-78.17%) and Chi-squared-for-trend (56,679, df=2) significant at P<10-500.
Monthly and daily use were linked with CVIR in bivariate geospatial regression models (P=0.0027, P=0.0059).
In multivariable additive models number of flight origins and population density were significant.
In interactive geospatial models adjusted for international travel, ethnicity, income, population, population density and drug use, terms including last month cannabis were significant from P=7.3x10-15, daily cannabis use from P=7.3x10-11 and last month cannabis was independently associated (P=0.0365).
Conclusions and Relevance.
Data indicate CVIR demonstrates significant trends across cannabis use intensity quintiles and with relaxed cannabis legislation.
Recent cannabis use is independently predictive of CVIR in bivariate and multivariable adjusted models and intensity of use is interactively significant.
Cannabis thus joins tobacco as a SARS2-CoV-2 risk factor.

Answer: {"verdict": "CONTRADICT", "evidence": ["Cannabis smoking is linked with poor respiratory health, immunosuppression and multiple contaminants.", "Potential synergism between the two epidemics would represent a major public health convergence.", "Cigarettes were implicated with disease severity in Wuhan, China."]}


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

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

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

Claim: It does not make a lot of sense that if somebody is otherwise healthy and young and they have hypertension alone, that they should be at increased risk

Abstract:
Since its recognition in December 2019, covid-19 has rapidly spread globally causing a pandemic.
Pre-existing comorbidities such as hypertension, diabetes, and cardiovascular disease are associated with a greater severity and higher fatality rate of covid-19.
Furthermore, covid-19 contributes to cardiovascular complications, including acute myocardial injury as a result of acute coronary syndrome, myocarditis, stress-cardiomyopathy, arrhythmias, cardiogenic shock, and cardiac arrest.
The cardiovascular interactions of covid-19 have similarities to that of severe acute respiratory syndrome, Middle East respiratory syndrome and influenza.
Specific cardiovascular considerations are also necessary in supportive treatment with anticoagulation, the continued use of renin-angiotensin-aldosterone system inhibitors, arrhythmia monitoring, immunosuppression or modulation, and mechanical circulatory support.

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: Covid-1 associated overexpressed prevotella proteins mediated host-pathogen interactions and their role in coronavirus outbreak

Abstract:
MOTIVATION: The outbreak of COVID-2019 initiated at Wuhan, China has become a global threat by rapid transmission and severe fatalities.
Recent studies have uncovered whole genome sequence of SARS-CoV-2 (causing COVID-2019).
In addition, lung metagenomic studies on infected patients revealed overrepresented Prevotella spp.
producing certain proteins in abundance.
We performed host-pathogen protein-protein interaction analysis between SARS-CoV-2 and overrepresented Prevotella proteins with human proteome.
We also performed functional overrepresentation analysis of interacting proteins to understand their role in COVID-2019 severity.
RESULTS: It was found that over-expressed Prevotella proteins can promote viral infection.
As per the results, Prevotella proteins, but not viral proteins are involved in multiple interactions with NF-kB, which is involved in increasing clinical severity of COVID-2019.
Prevotella may have role in COVID-2019 outbreak and should be given importance for understanding disease mechanisms and improving treatment outcomes.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Answer: {"verdict": "CONTRADICT", "evidence": ["As per the results, Prevotella proteins, but not viral proteins are involved in multiple interactions with NF-kB, which is involved in increasing clinical severity of COVID-2019.", "Prevotella may have role in COVID-2019 outbreak and should be given importance for understanding disease mechanisms and improving treatment outcomes."]}


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: An ultra-potent synthetic nanobody neutralizes sars-cov-2 by locking mutations into an inactive conformation

Abstract:
Without an effective prophylactic solution, infections from SARS-CoV-2 continue to rise worldwide with devastating health and economic costs.
SARS-CoV-2 gains entry into host cells via an interaction between its Spike protein and the host cell receptor angiotensin converting enzyme 2 (ACE2).
Disruption of this interaction confers potent neutralization of viral entry, providing an avenue for vaccine design and for therapeutic antibodies.
Here, we develop single-domain antibodies (nanobodies) that potently disrupt the interaction between the SARS-CoV-2 Spike and ACE2.
By screening a yeast surface-displayed library of synthetic nanobody sequences, we identified a panel of nanobodies that bind to multiple epitopes on Spike and block ACE2 interaction via two distinct mechanisms.
Cryogenic electron microscopy (cryo-EM) revealed that one exceptionally stable nanobody, Nb6, binds Spike in a fully inactive conformation with its receptor binding domains (RBDs) locked into their inaccessible down-state, incapable of binding ACE2.
Affinity maturation and structure-guided design of multivalency yielded a trivalent nanobody, mNb6-tri, with femtomolar affinity for SARS-CoV-2 Spike and picomolar neutralization of SARS-CoV-2 infection.
mNb6-tri retains stability and function after aerosolization, lyophilization, and heat treatment.
These properties may enable aerosol-mediated delivery of this potent neutralizer directly to the airway epithelia, promising to yield a widely deployable, patient-friendly prophylactic and/or early infection therapeutic agent to stem the worst pandemic in a century.

Answer: {"verdict": "CONTRADICT", "evidence": ["Cryogenic electron microscopy (cryo-EM) revealed that one exceptionally stable nanobody, Nb6, binds Spike in a fully inactive conformation with its receptor binding domains (RBDs) locked into their inaccessible down-state, incapable of binding ACE2."]}


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: In other words, the SARS-CoV-2 stool analysis is not diagnostic of COVID-19.

Abstract:
The recently emerged SARS-CoV-2 (Coronaviridae; Betacoronavirus) is the underlying cause of COVID-19 disease.
Here we assessed SARS-CoV2 from the Kingdom of Saudi Arabia alongside sequences of SARS-CoV, bat SARS-like CoVs and MERS-CoV, the latter currently detected in this region.
Phylogenetic analysis, natural selection investigation and genome recombination analysis were performed.
Our analysis showed that all Saudi SARS-CoV-2 sequences are of the same origin and closer proximity to bat SARS-like CoVs, followed by SARS-CoVs, however quite distant to MERS-CoV. Moreover, genome recombination analysis revealed two recombination events between SARS-CoV-2 and bat SARS-like CoVs.
This was further assessed by S gene recombination analysis.
These recombination events may be relevant to the emergence of this novel virus.
Moreover, positive selection pressure was detected between SARS-CoV-2, bat SL-CoV isolates and human SARS-CoV isolates.
However, the highest positive selection occurred between SARS-CoV-2 isolates and 2 bat-SL-CoV isolates (Bat-SL-RsSHC014 and Bat-SL-CoVZC45).
This further indicates that SARS-CoV-2 isolates were adaptively evolved from bat SARS-like isolates, and that a virus with originating from bats triggered this pandemic.
This study thuds sheds further light on the origin of this virus.
AUTHOR SUMMARY The emergence and subsequent pandemic of SARS-CoV-2 is a unique challenge to countries all over the world, including Saudi Arabia where cases of the related MERS are still being reported.
Saudi SARS-CoV-2 sequences were found to be likely of the same or similar origin.
In our analysis, SARS-CoV-2 were more closely related to bat SARS-like CoVs rather than to MERS-CoV (which originated in Saudi Arabia) or SARS-CoV, confirming other phylogenetic efforts on this pathogen.
Recombination and positive selection analysis further suggest that bat coronaviruses may be at the origin of SARS-CoV-2 sequences.
The data shown here give hints on the origin of this virus and may inform efforts on transmissibility, host adaptation and other biological aspects of this virus.

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

Abstract:
BACKGROUND: The current COVID-19 pandemic, caused by SARS-CoV-2, has emerged as a public health emergency.
All nations are seriously challenged as the virus spreads rapidly across the globe with no regard for borders.
The primary management of IBD involves treating uncontrolled inflammation with most patients requiring immune-based therapies.
However, these therapies may weaken the immune system and potentially place IBD patients at increased risk of infections and infectious complications including those from COVID-19.
AIM: To summarise the scale of the COVID-19 pandemic, review unique concerns regarding IBD management and infection risk during the pandemic and assess COVID-19 management options and drug interactions in the IBD population.
METHODS: A literature review on IBD, SARS-CoV-2 and COVID-19 was undertaken and relevant literature was summarised and critically examined.
RESULTS: IBD patients do not appear to be more susceptible to SARS-CoV-2 infection and there is no evidence of an association between IBD therapies and increased risk of COVID-19.
IBD medication adherence should be encouraged to prevent disease flare but where possible high-dose systemic corticosteroids should be avoided.
Patients should exercise social distancing, optimise co-morbidities and be up to date with influenza and pneumococcal vaccines.
If a patient develops COVID-19, immune suppressing medications should be withheld until infection resolution and if trial medications for COVID-19 are being considered, potential drug interactions should be checked.
CONCLUSIONS: IBD patient management presents a challenge in the current COVID-19 pandemic.
The primary focus should remain on keeping bowel inflammation controlled and encouraging medication adherence.

Answer: {"verdict": "SUPPORT", "evidence": ["However, these therapies may weaken the immune system and potentially place IBD patients at increased risk of infections and infectious complications including those from 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: Adding pepper to your soup or other meals does not prevent or cure COVID-19.

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

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


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

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

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

Claim: Vitamins C and D boost our immune systems, aiding in the fight against infectious diseases;

Abstract:
The novel coronavirus Covid-19 follows transmission route and clinical presentation of all community-acquired coronaviruses.
Instead, the rate of transmission is significative higher, with a faster spread of the virus responsible of the worldwide outbreak and a significative higher mortality rate due to the development of a severe lung injury.
Most noteworthy is the distribution of death rate among age groups.
Children and younger people are almost protected from severe clinical presentation.
Possible explanation of this phenomenon could be the ability of past vaccinations (especially tetanic, diphtheria toxoids and inactivated bacteria as pertussis) to stimulate immune system and to generate a scattered immunity against non-self antigens in transit, as coronaviruses and other community-circulating viruses and make immune system readier to develop specific immunity against Covid-19.
The first support to this hypothesis is the distribution of mortality rate during historical pandemics ("Spanish flu" 1918, "Asian flu" 1956 and "the Hong Kong flu" 1968) among age groups before and after the introduction of vaccines.
The immunological support to the hypothesis derives from recent studies about immunotherapy for malignancies, which propose the use of oncolytic vaccines combined with toxoids in order to exploit CD4 + memory T cell recall in supporting the ongoing anti-tumour response.
According to this hypothesis vaccine formulations (tetanus, diphtheria, Bordetella pertussis) could be re-administrate after the first contact with Covid-19, better before the development of respiratory severe illness and of course before full-blown ARDS (Acute Respiratory Distress Syndrome).
The CD4 + memory exploiting could help immune system to recall immunity of already know antigens against coronaviruses, avoiding or limiting "lung crash" until virus specific immunity develops and making it faster and prolonged.
Finally, this administration could be helpful not only in already infected patients, but also before infection.
In fact, people could have an immune system more ready when the contact with the Covid-19 will occur.

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: the virus spreads mainly through small airborne droplets when an infected person coughs or sneezes.

Abstract:
Social distancing measures, with varying degrees of restriction, have been imposed around the world in order to stem the spread of COVID-19.
In this work we analyze the effect of current social distancing measures in the United States.
We quantify the reduction in doubling rate, by state, that is associated with social distancing.
We find that social distancing is associated with a statistically-significant reduction in the doubling rate for all but three states.
At the same time, we do not find significant evidence that social distancing has resulted in a reduction in the number of daily confirmed cases.
Instead, social distancing has merely stabilized the spread of the disease.
We provide an illustration of our findings for each state, including point estimates of the effective reproduction number, R, both with and without social distancing.
We also discuss the policy implications of our findings.

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: Coronaviruses cause respiratory illnesses, so the lungs are usually affected first. Early symptoms include fever, cough, and shortness of breath.

Abstract:
The novel coronavirus Covid-19 follows transmission route and clinical presentation of all community-acquired coronaviruses.
Instead, the rate of transmission is significative higher, with a faster spread of the virus responsible of the worldwide outbreak and a significative higher mortality rate due to the development of a severe lung injury.
Most noteworthy is the distribution of death rate among age groups.
Children and younger people are almost protected from severe clinical presentation.
Possible explanation of this phenomenon could be the ability of past vaccinations (especially tetanic, diphtheria toxoids and inactivated bacteria as pertussis) to stimulate immune system and to generate a scattered immunity against non-self antigens in transit, as coronaviruses and other community-circulating viruses and make immune system readier to develop specific immunity against Covid-19.
The first support to this hypothesis is the distribution of mortality rate during historical pandemics ("Spanish flu" 1918, "Asian flu" 1956 and "the Hong Kong flu" 1968) among age groups before and after the introduction of vaccines.
The immunological support to the hypothesis derives from recent studies about immunotherapy for malignancies, which propose the use of oncolytic vaccines combined with toxoids in order to exploit CD4 + memory T cell recall in supporting the ongoing anti-tumour response.
According to this hypothesis vaccine formulations (tetanus, diphtheria, Bordetella pertussis) could be re-administrate after the first contact with Covid-19, better before the development of respiratory severe illness and of course before full-blown ARDS (Acute Respiratory Distress Syndrome).
The CD4 + memory exploiting could help immune system to recall immunity of already know antigens against coronaviruses, avoiding or limiting "lung crash" until virus specific immunity develops and making it faster and prolonged.
Finally, this administration could be helpful not only in already infected patients, but also before infection.
In fact, people could have an immune system more ready when the contact with the Covid-19 will occur.

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: While there is very limited data (and none specific for COVID-19), the following cocktail may have a role in the prevention/mitigation of COVID-19 disease. Vitamin C 500 mg BID and Quercetin 250 mg daily Zinc 75-100 mg/day

Abstract:
BACKGROUND The coronavirus disease 2019 (COVID-19) pandemic has affected almost 2.5 million people worldwide with almost 170 000 deaths reported to date.
So far, there is scarce evidence for the current treatment options available for COVID-19.
Vitamin C has previously been used for treatment of severe sepsis and septic shock.
We reviewed the feasibility of using vitamin C in the setting of COVID-19 in a series of patients.
METHODS We sequentially identified a series of patients who were requiring at least 30% of FiO2 or more who received IV vitamin C as part of the COVID-19 treatment and analyzed their demographic and clinical characteristics.
We compared inflammatory markers pre and post treatment including D-dimer and ferritin.
RESULTS We identified a total of 17 patients who received IV vitamin C for COVID-19.
The inpatient mortality rate in this series was 12% with 17.6% rates of intubation and mechanical ventilation.
We noted a significant decrease in inflammatory markers, including ferritin and D-dimer, and a trend to decreasing FiO2 requirements, after vitamin C administration.
CONCLUSION The use of IV vitamin C in patients with moderate to severe COVID-19 disease may be feasible.

Answer: {"verdict": "SUPPORT", "evidence": ["RESULTS We identified a total of 17 patients who received IV vitamin C for COVID-19.", "The inpatient mortality rate in this series was 12% with 17.6% rates of intubation and mechanical ventilation.", "We noted a significant decrease in inflammatory markers, including ferritin and D-dimer, and a trend to decreasing FiO2 requirements, after vitamin C administration.", "CONCLUSION The use of IV vitamin C in patients with moderate to severe COVID-19 disease may be feasible."]}


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: Evolutionary arms race between virus and host drives genetic diversity in bat sars related coronavirus spike genes

Abstract:
The Chinese horseshoe bat (Rhinolophus sinicus), reservoir host of severe acute respiratory syndrome coronavirus (SARS-CoV), carries many bat SARS-related CoVs (SARSr-CoVs) with high genetic diversity, particularly in the spike gene.
Despite these variations, some bat SARSr-CoVs can utilize the orthologs of the human SARS-CoV receptor, angiotensin-converting enzyme 2 (ACE2), for entry.
It is speculated that the interaction between bat ACE2 and SARSr-CoV spike proteins drives diversity.
Here, we identified a series of R. sinicus ACE2 variants with some polymorphic sites involved in the interaction with the SARS-CoV spike protein.
Pseudoviruses or SARSr-CoVs carrying different spike proteins showed different infection efficiencies in cells transiently expressing bat ACE2 variants.
Consistent results were observed by binding affinity assays between SARS-CoV and SARSr-CoV spike proteins and receptor molecules from bats and humans.
All tested bat SARSr-CoV spike proteins had a higher binding affinity to human ACE2 than to bat ACE2, although they showed a 10-fold lower binding affinity to human ACE2 compared with that of their SARS-CoV counterpart.
Structure modeling revealed that the difference in binding affinity between spike and ACE2 might be caused by the alteration of some key residues in the interface of these two molecules.
Molecular evolution analysis indicates that some key residues were under positive selection.
These results suggest that the SARSr-CoV spike protein and R. sinicus ACE2 may have coevolved over time and experienced selection pressure from each other, triggering the evolutionary arms race dynamics.
IMPORTANCE Evolutionary arms race dynamics shape the diversity of viruses and their receptors.
Identification of key residues which are involved in interspecies transmission is important to predict potential pathogen spillover from wildlife to humans.
Previously, we have identified genetically diverse SARSr-CoVs in Chinese horseshoe bats.
Here, we show the highly polymorphic ACE2 in Chinese horseshoe bat populations.
These ACE2 variants support SARS-CoV and SARSr-CoV infection but with different binding affinities to different spike proteins.
The higher binding affinity of SARSr-CoV spike to human ACE2 suggests that these viruses have the capacity for spillover to humans.
The positive selection of residues at the interface between ACE2 and SARSr-CoV spike protein suggests long-term and ongoing coevolutionary dynamics between them.
Continued surveillance of this group of viruses in bats is necessary for the prevention of the next SARS-like disease.

Answer: {"verdict": "SUPPORT", "evidence": ["It is speculated that the interaction between bat ACE2 and SARSr-CoV spike proteins drives diversity.", "These results suggest that the SARSr-CoV spike protein and R. sinicus ACE2 may have coevolved over time and experienced selection pressure from each other, triggering the evolutionary arms race dynamics."]}


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

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

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

Claim: Covid-19 kills also young people

Abstract:
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": []}