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Modeling shield immunity to reduce COVID-19 epidemic spread.

ABSTRACT: The COVID-19 pandemic has precipitated a global crisis, with more than 1,430,000 confirmed cases and more than 85,000 confirmed deaths globally as of 9 April 2020^1-4. Mitigation and suppression of new infections have emerged as the two predominant public health control strategies⁵. Both strategies focus on reducing new infections by limiting human-to-human interactions, which could be both socially and economically unsustainable in the long term. We have developed and analyzed an epidemiological intervention model that leverages serological tests^6,7 to identify and deploy recovered individuals⁸ as focal points for sustaining safer interactions via interaction substitution, developing what we term 'shield immunity' at the population scale. The objective of a shield immunity strategy is to help to sustain the interactions necessary for the functioning of essential goods and services⁹ while reducing the probability of transmission. Our shield immunity approach could substantively reduce the length and reduce the overall burden of the current outbreak, and can work synergistically with social distancing. The present model highlights the value of serological testing as part of intervention strategies, in addition to its well-recognized roles in estimating prevalence^10,11 and in the potential development of plasma-based therapies^12-15.

SUBMITTER: Weitz JS

PROVIDER: S-EPMC8272982 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Modeling shield immunity to reduce COVID-19 epidemic spread.

Weitz Joshua S JS Beckett Stephen J SJ Coenen Ashley R AR Demory David D Dominguez-Mirazo Marian M Dushoff Jonathan J Leung Chung-Yin CY Li Guanlin G Măgălie Andreea A Park Sang Woo SW Rodriguez-Gonzalez Rogelio R Shivam Shashwat S Zhao Conan Y CY

Nature medicine 20200507 6

The COVID-19 pandemic has precipitated a global crisis, with more than 1,430,000 confirmed cases and more than 85,000 confirmed deaths globally as of 9 April 2020<sup>1-4</sup>. Mitigation and suppression of new infections have emerged as the two predominant public health control strategies<sup>5</sup>. Both strategies focus on reducing new infections by limiting human-to-human interactions, which could be both socially and economically unsustainable in the long term. We have developed and analy ...[more]

PMID: 32382154

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Project description:BackgroundThe COVID-19 pandemic has caused serious health, economic, and social consequences worldwide. Understanding how infectious diseases spread can help mitigate these impacts. The Theil index, a measure of inequality rooted in information theory, is useful for identifying geographic disproportionality in COVID-19 incidence across regions.ObjectiveThis study focused on capturing the degrees of regional disproportionality in incidence rates of infectious diseases over time. Using the Theil index, we aim to assess regional disproportionality in the spread of COVID-19 and detect epicenters where the number of infected individuals was disproportionately concentrated.MethodsTo quantify the degree of disproportionality in the incidence rates, we applied the Theil index to the publicly available data of daily confirmed COVID-19 cases in the United States over a 1100-day period. This index measures relative disproportionality by comparing daily regional case distributions with population proportions, thereby identifying regions where infections are disproportionately concentrated.ResultsOur analysis revealed a dynamic pattern of regional disproportionality in the confirmed cases by monitoring variations in regional contributions to the Theil index as the pandemic progressed. Over time, the index reflected a transition from localized outbreaks to widespread transmission, with high values corresponding to concentrated cases in some regions. We also found that the peaks in the Theil index often preceded surges in confirmed cases, suggesting its potential utility as an early warning signal.ConclusionsThis study demonstrated that the Theil index is one of the effective indices for quantifying regional disproportionality in COVID-19 incidence rates. Although the Theil index alone cannot fully capture all aspects of pandemic dynamics, it serves as a valuable tool when used alongside other indicators such as infection and hospitalization rates. This approach allows policy makers to monitor regional disproportionality efficiently, offering insights for early intervention and targeted resource allocation.

Dataset Information

Modeling shield immunity to reduce COVID-19 epidemic spread.

Publications

Modeling shield immunity to reduce COVID-19 epidemic spread.

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