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Relieving Cost of Epidemic by Parrondo's Paradox: A COVID-19 Case Study.

ABSTRACT: COVID-19, also known as SARS-CoV-2, is a coronavirus that is highly pathogenic and virulent. It spreads very quickly through close contact, and so in response to growing numbers of cases, many countries have imposed lockdown measures to slow its spread around the globe. The purpose of a lockdown is to reduce reproduction, that is, the number of people each confirmed case infects. Lockdown measures have worked to varying extents but they come with a massive price. Nearly every individual, community, business, and economy has been affected. In this paper, switching strategies that take into account the total "cost" borne by a community in response to COVID-19 are proposed. The proposed cost function takes into account the health and well-being of the population, as well as the economic impact due to the lockdown. The model allows for a comparative study to investigate the effectiveness of various COVID-19 suppression strategies. It reveals that both the strategy to implement a lockdown and the strategy to maintain an open community are individually losing in terms of the total "cost" per day. However, switching between these two strategies in a certain manner can paradoxically lead to a winning outcome-a phenomenon attributed to Parrondo's paradox.

SUBMITTER: Cheong KH

PROVIDER: S-EPMC7740105 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Relieving Cost of Epidemic by Parrondo's Paradox: A COVID-19 Case Study.

Cheong Kang Hao KH Wen Tao T Lai Joel Weijia JW

Advanced science (Weinheim, Baden-Wurttemberg, Germany) 20201105 24

COVID-19, also known as SARS-CoV-2, is a coronavirus that is highly pathogenic and virulent. It spreads very quickly through close contact, and so in response to growing numbers of cases, many countries have imposed lockdown measures to slow its spread around the globe. The purpose of a lockdown is to reduce reproduction, that is, the number of people each confirmed case infects. Lockdown measures have worked to varying extents but they come with a massive price. Nearly every individual, communi ...[more]

PMID: 33344130

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Project description:BackgroundSince the beginning of the COVID-19 pandemic, researchers and health authorities have sought to identify the different parameters that drive its local transmission cycles to make better decisions regarding prevention and control measures. Different modeling approaches have been proposed in an attempt to predict the behavior of these local cycles.ObjectiveThis paper presents a framework to characterize the different variables that drive the local, or epidemic, cycles of the COVID-19 pandemic, in order to provide a set of relatively simple, yet efficient, statistical tools to be used by local health authorities to support decision making.MethodsVirtually closed cycles were compared to cycles in progress from different locations that present similar patterns in the figures that describe them. With the aim to compare populations of different sizes at different periods of time and locations, the cycles were normalized, allowing an analysis based on the core behavior of the numerical series. A model for the reproduction number was derived from the experimental data, and its performance was presented, including the effect of subnotification (ie, underreporting). A variation of the logistic model was used together with an innovative inventory model to calculate the actual number of infected persons, analyze the incubation period, and determine the actual onset of local epidemic cycles.ResultsThe similarities among cycles were demonstrated. A pattern between the cycles studied, which took on a triangular shape, was identified and used to make predictions about the duration of future cycles. Analyses on effective reproduction number (Rt) and subnotification effects for Germany, Italy, and Sweden were presented to show the performance of the framework introduced here. After comparing data from the three countries, it was possible to determine the probable dates of the actual onset of the epidemic cycles for each country, the typical duration of the incubation period for the disease, and the total number of infected persons during each cycle. In general terms, a probable average incubation time of 5 days was found, and the method used here was able to estimate the end of the cycles up to 34 days in advance, while demonstrating that the impact of the subnotification level (ie, error) on the effective reproduction number was <5%.ConclusionsIt was demonstrated that, with relatively simple mathematical tools, it is possible to obtain a reliable understanding of the behavior of COVID-19 local epidemic cycles, by introducing an integrated framework for identifying cycle patterns and calculating the variables that drive it, namely: the Rt, the subnotification effects on estimations, the most probable actual cycles start dates, the total number of infected, and the most likely incubation period for SARS-CoV-2.

Project description:BackgroundHealth-care resource constraints in low-income and middle-income countries necessitate the identification of cost-effective public health interventions to address COVID-19. We aimed to develop a dynamic COVID-19 microsimulation model to assess clinical and economic outcomes and cost-effectiveness of epidemic control strategies in KwaZulu-Natal province, South Africa.MethodsWe compared different combinations of five public health interventions: health-care testing alone, where diagnostic testing is done only for individuals presenting to health-care centres; contact tracing in households of cases; isolation centres, for cases not requiring hospital admission; mass symptom screening and molecular testing for symptomatic individuals by community health-care workers; and quarantine centres, for household contacts who test negative. We calibrated infection transmission rates to match effective reproduction number (Re) estimates reported in South Africa. We assessed two main epidemic scenarios for a period of 360 days, with an Re of 1·5 and 1·2. Strategies with incremental cost-effectiveness ratio (ICER) of less than US$3250 per year of life saved were considered cost-effective. We also did sensitivity analyses by varying key parameters (Re values, molecular testing sensitivity, and efficacies and costs of interventions) to determine the effect on clinical and cost projections.FindingsWhen Re was 1·5, health-care testing alone resulted in the highest number of COVID-19 deaths during the 360-day period. Compared with health-care testing alone, a combination of health-care testing, contact tracing, use of isolation centres, mass symptom screening, and use of quarantine centres reduced mortality by 94%, increased health-care costs by 33%, and was cost-effective (ICER $340 per year of life saved). In settings where quarantine centres were not feasible, a combination of health-care testing, contact tracing, use of isolation centres, and mass symptom screening was cost-effective compared with health-care testing alone (ICER $590 per year of life saved). When Re was 1·2, health-care testing, contact tracing, use of isolation centres, and use of quarantine centres was the least costly strategy, and no other strategies were cost-effective. In sensitivity analyses, a combination of health-care testing, contact tracing, use of isolation centres, mass symptom screening, and use of quarantine centres was generally cost-effective, with the exception of scenarios in which Re was 2·6 and when efficacies of isolation centres and quarantine centres for transmission reduction were reduced.InterpretationIn South Africa, strategies involving household contact tracing, isolation, mass symptom screening, and quarantining household contacts who test negative would substantially reduce COVID-19 mortality and would be cost-effective. The optimal combination of interventions depends on epidemic growth characteristics and practical implementation considerations.FundingUS National Institutes of Health, Royal Society, Wellcome Trust.

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Relieving Cost of Epidemic by Parrondo's Paradox: A COVID-19 Case Study.

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Relieving Cost of Epidemic by Parrondo's Paradox: A COVID-19 Case Study.

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