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Global scenario, public health concerns and mitigation strategies to counter current ongoing SARS-CoV-2 / COVID-19 pandemic.

ABSTRACT: Severe acute respiratory syndrome Coronavirus- 2 (SARS-CoV-2), the etiological agent of the novel coronavirus disease (COVID-19), has posed a great public health threat to the global community as a pandemic. The origin of the virus has been linked to animals, through a yet-to-be-identified intermediate host. The disease is transmitted to humans mainly through inhalation or contact with infected droplets. The variable clinical presentation of COVID-19 includes fever, cough, sore throat, breathlessness, fatigue and malaise; however, cutaneous, ocular, neurological, and gastrointestinal manifestations have also been reported. There is an urgent need to strengthen One Health surveillance, intervention, and management strategies to understand the ecology of coronaviruses and to prevent epidemics in the future. Global attention toward the development of treatments, immunotherapies, vaccines, and control options to combat the COVID-19 pandemic has been on an increasing trend. Here, we review the current epidemiological status, public health concerns, and mitigation strategies for COVID-19.

SUBMITTER: Barbuddhe SB

PROVIDER: S-EPMC7605515 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundUnprecedented public health measures have been used during this coronavirus 2019 (COVID-19) pandemic to control the spread of SARS-CoV-2 virus. It is a challenge to implement timely and appropriate public health interventions.Methods and findingsPopulation and COVID-19 epidemiological data between 21st January 2020 to 15th November 2020 from 216 countries and territories were included with the implemented public health interventions. We used deep reinforcement learning, and the algorithm was trained to enable agents to try to find optimal public health strategies that maximized total reward on controlling the spread of COVID-19. The results suggested by the algorithm were analyzed against the actual timing and intensity of lockdown and travel restrictions. Early implementations of the actual lockdown and travel restriction policies, usually at the time of local index case were associated with less burden of COVID-19. In contrast, our agent suggested to initiate at least minimal intensity of lockdown or travel restriction even before or on the day of the index case in each country and territory. In addition, the agent mostly recommended a combination of lockdown and travel restrictions and higher intensity policies than the policies implemented by governments, but did not always encourage rapid full lockdown and full border closures. The limitation of this study was that it was done with incomplete data due to the emerging COVID-19 epidemic, inconsistent testing and reporting. In addition, our research focuses only on population health benefits by controlling the spread of COVID-19 without balancing the negative impacts of economic and social consequences.InterpretationCompared to actual government implementation, our algorithm mostly recommended earlier intensity of lockdown and travel restrictions. Reinforcement learning may be used as a decision support tool for implementation of public health interventions during COVID-19 and future pandemics.

Project description:BackgroundThe threat of emergence of a human-to-human transmissible strain of highly pathogenic influenza A(H5N1) is very real, and is reinforced by recent results showing that genetically modified A(H5N1) may be readily transmitted between ferrets. Public health authorities are hesitant in introducing social distancing interventions due to societal disruption and productivity losses. This study estimates the effectiveness and total cost (from a societal perspective, with a lifespan time horizon) of a comprehensive range of social distancing and antiviral drug strategies, under a range of pandemic severity categories.MethodsAn economic analysis was conducted using a simulation model of a community of ~30,000 in Australia. Data from the 2009 pandemic was used to derive relationships between the Case Fatality Rate (CFR) and hospitalization rates for each of five pandemic severity categories, with CFR ranging from 0.1% to 2.5%.ResultsFor a pandemic with basic reproduction number R0 = 1.8, adopting no interventions resulted in total costs ranging from $441 per person for a pandemic at category 1 (CFR 0.1%) to $8,550 per person at category 5 (CFR 2.5%). For severe pandemics of category 3 (CFR 0.75%) and greater, a strategy combining antiviral treatment and prophylaxis, extended school closure and community contact reduction resulted in the lowest total cost of any strategy, costing $1,584 per person at category 5. This strategy was highly effective, reducing the attack rate to 5%. With low severity pandemics costs are dominated by productivity losses due to illness and social distancing interventions, whereas higher severity pandemic costs are dominated by healthcare costs and costs arising from productivity losses due to death.ConclusionsFor pandemics in high severity categories the strategies with the lowest total cost to society involve rigorous, sustained social distancing, which are considered unacceptable for low severity pandemics due to societal disruption and cost.

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Global scenario, public health concerns and mitigation strategies to counter current ongoing SARS-CoV-2 / COVID-19 pandemic.

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