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1. Importance of social inequalities to contact patterns, vaccine uptake, and epidemic dynamics

   https://doi.org/10.1038/s41467-024-48332-y  

   Manna, Adriana; Koltai, Júlia; Karsai, Márton (December 2024, Nature Communications)

   Abstract Individuals’ socio-demographic and economic characteristics crucially shape the spread of an epidemic by largely determining the exposure level to the virus and the severity of the disease for those who got infected. While the complex interplay between individual characteristics and epidemic dynamics is widely recognised, traditional mathematical models often overlook these factors. In this study, we examine two important aspects of human behaviour relevant to epidemics: contact patterns and vaccination uptake. Using data collected during the COVID-19 pandemic in Hungary, we first identify the dimensions along which individuals exhibit the greatest variation in their contact patterns and vaccination uptake. We find that generally higher socio-economic groups of the population have a higher number of contacts and a higher vaccination uptake with respect to disadvantaged groups. Subsequently, we propose a data-driven epidemiological model that incorporates these behavioural differences. Finally, we apply our model to analyse the fourth wave of COVID-19 in Hungary, providing valuable insights into real-world scenarios. By bridging the gap between individual characteristics and epidemic spread, our research contributes to a more comprehensive understanding of disease dynamics and informs effective public health strategies. 

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2. Strategic vaccine stockpiles for regional epidemics of emerging viruses: A geospatial modeling framework

   https://doi.org/10.1016/j.vaccine.2024.06.019  

   Carlson, Colin J; Garnier, Romain; Tiu, Andrew; Luby, Stephen P; Bansal, Shweta (October 2024, Vaccine)

   Multinational epidemics of emerging infectious diseases are increasingly common, due to anthropogenic pressure on ecosystems and the growing connectivity of human populations. Early and efficient vaccination can contain outbreaks and prevent mass mortality, but optimal vaccine stockpiling strategies are dependent on pathogen characteristics, reservoir ecology, and epidemic dynamics. Here, we model major regional outbreaks of Nipah virus and Middle East respiratory syndrome, and use these to develop a generalized framework for estimating vaccine stockpile needs based on spillover geography, spatially-heterogeneous healthcare capacity and spatially-distributed human mobility networks. Because outbreak sizes were highly skewed, we found that most outbreaks were readily contained (median stockpile estimate for MERS-CoV: 2,089 doses; Nipah: 1,882 doses), but the maximum estimated stockpile need in a highly unlikely large outbreak scenario was 2–3 orders of magnitude higher (MERS-CoV: ~87,000 doses; Nipah ~ 1.1 million doses). Sensitivity analysis revealed that stockpile needs were more dependent on basic epidemiological parameters (i.e., death and recovery rate) and healthcare availability than any uncertainty related to vaccine efficacy or deployment strategy. Our results highlight the value of descriptive epidemiology for real-world modeling applications, and suggest that stockpile allocation should consider ecological, epidemiological, and social dimensions of risk. 

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3. Protect or prevent? A practicable framework for the dilemmas of COVID-19 vaccine prioritization

   https://doi.org/10.1371/journal.pone.0316294  

   Arghal, Raghu; Rubin, Harvey; Saeedi_Bidokhti, Shirin; Sarkar, Saswati (January 2025, PLOS ONE)

   Ekwebelem, Osmond (Ed.)

   Determining COVID-19 vaccination strategies presents many challenges in light of limited vaccination capacity and the heterogeneity of affected communities. Who should be prioritized for early vaccination when different groups manifest different levels of risks and contact rates? Answering such questions often becomes computationally intractable given that network size can exceed millions. We obtain a framework to compute the optimal vaccination strategy within seconds to minutes from among all strategies, including highly dynamic ones that adjust vaccine allocation as often as required, and even with modest computation resources. We then determine the optimal strategy for a large range of parameter values representative of various US states, countries, and case studies including retirement homes and prisons. The optimal is almost always one of a few candidate strategies, and, even when not, the suboptimality of the best among these candidates is minimal. Further, we find that many commonly deployed vaccination strategies, such as vaccinating the high risk group first, or administering second doses without delay, can often incur higher death rates, hospitalizations, and symptomatic infection counts. Our framework can be easily adapted to future variants or pandemics through appropriate choice of the compartments of the disease and parameters. 

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4. Variation in primate decision-making under uncertainty and the roots of human economic behaviour

   https://doi.org/10.1098/rstb.2019.0671  

   De Petrillo, Francesca; Rosati, Alexandra G. (March 2021, Philosophical Transactions of the Royal Society B: Biological Sciences)

   null (Ed.)

   Uncertainty is a ubiquitous component of human economic behaviour, yet people can vary in their preferences for risk across populations, individuals and different points in time. As uncertainty also characterizes many aspects of animal decision-making, comparative research can help evaluate different potential mechanisms that generate this variation, including the role of biological differences or maturational change versus cultural learning, as well as identify human-unique components of economic decision-making. Here, we examine decision-making under risk across non-human primates, our closest relatives. We first review theoretical approaches and current methods for understanding decision-making in animals. We then assess the current evidence for variation in animal preferences between species and populations, between individuals based on personality, sex and age, and finally, between different contexts and individual states. We then use these primate data to evaluate the processes that can shape human decision-making strategies and identify the primate foundations of human economic behaviour. This article is part of the theme issue ‘Existence and prevalence of economic behaviours among non-human primates’. 

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5. Dynamic prioritization of COVID-19 vaccines when social distancing is limited for essential workers

   https://doi.org/10.1073/pnas.2025786118  

   Buckner, Jack H.; Chowell, Gerardo; Springborn, Michael R. (April 2021, Proceedings of the National Academy of Sciences)

   null (Ed.)

   COVID-19 vaccines have been authorized in multiple countries, and more are under rapid development. Careful design of a vaccine prioritization strategy across sociodemographic groups is a crucial public policy challenge given that 1) vaccine supply will be constrained for the first several months of the vaccination campaign, 2) there are stark differences in transmission and severity of impacts from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) across groups, and 3) SARS-CoV-2 differs markedly from previous pandemic viruses. We assess the optimal allocation of a limited vaccine supply in the United States across groups differentiated by age and essential worker status, which constrains opportunities for social distancing. We model transmission dynamics using a compartmental model parameterized to capture current understanding of the epidemiological characteristics of COVID-19, including key sources of group heterogeneity (susceptibility, severity, and contact rates). We investigate three alternative policy objectives (minimizing infections, years of life lost, or deaths) and model a dynamic strategy that evolves with the population epidemiological status. We find that this temporal flexibility contributes substantially to public health goals. Older essential workers are typically targeted first. However, depending on the objective, younger essential workers are prioritized to control spread or seniors to directly control mortality. When the objective is minimizing deaths, relative to an untargeted approach, prioritization averts deaths on a range between 20,000 (when nonpharmaceutical interventions are strong) and 300,000 (when these interventions are weak). We illustrate how optimal prioritization is sensitive to several factors, most notably, vaccine effectiveness and supply, rate of transmission, and the magnitude of initial infections. 

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