Publications
Peer-reviewed and other publications in reverse chronological order.
2025
- Incorporating Authority Perception, Economic Status, and Behavioral Response in Infectious Disease ControlHuaning Liu, Junke Yang, Soren L Larsen, Pamela P Martinez, and Gokce DayanikliarXiv preprint arXiv:2512.23188, 2025
We introduce a multi-population mean field game framework to examine how economic status and authority perception shape vaccination and social distancing decisions under different epidemic control policies. We carried out a survey to inform our model and stratify the population into six groups based on income and perception of authority, capturing behavioral heterogeneity. Individuals adjust their socialization and vaccination levels to optimize objectives such as minimizing treatment costs, complying with social-distancing guidelines if they are authority-followers, or reducing losses from decreased social interactions if they are authority-indifferents, alongside economic costs. Public health authorities influence behavior through social-distancing guidelines and vaccination costs. We characterize the Nash equilibrium via a forward-backward differential equation system, provide its mathematical analysis, and develop a numerical algorithm to solve it. Our findings reveal a trade-off between social-distancing and vaccination decisions. Under stricter guidelines that target both susceptible and infected individuals, followers reduce both socialization and vaccination levels, while indifferents increase socialization due to followers’ preventative measures. Adaptive guidelines targeting infected individuals effectively reduce infections and narrow the gap between low- and high-income groups, even when susceptible individuals socialize more and vaccinate less. Lower vaccination costs incentivize vaccination among low-income groups, but their impact on disease spread is smaller than when they are coupled with social-distancing guidelines. Trust-building emerges as a critical factor in epidemic mitigation, underscoring the importance of data-informed, game-theoretical models that aim to understand complex human responses to mitigation policies.
- Influence of immune history when choosing a SARS-CoV-2 booster strategySoren L Larsen, Iffat Noor, Haylee West, Eliana Chandra, Pamela P Martinez, and Alicia NM KraayScientific reports, 2025
Given the continued emergence of SARS-CoV-2 variants of concern as well as unprecedented vaccine development, it is crucial to understand the effect of updated vaccine formulations at the population level. While bivalent formulations developed during 2022 have had higher efficacy in vaccine trials, translating these findings to real-world effectiveness is challenging due to diversity in immune history, especially in settings with a high degree of natural immunity. Known socioeconomic disparities in key metrics such as vaccine coverage, social distancing, and access to healthcare have likely shaped the development and distribution of this immune landscape. Yet little has been done to investigate the impact of booster formulation in the context of host heterogeneity. Here, we present work undertaken in 2022-2023 to inform the World Health Organization’s Immunization and Vaccines Related Implementation Research Advisory Committee (IVIR-AC), at a time when policymakers were considering optimal boosting strategies. Using two complementary mathematical models that capture host demographics and immune histories over time, we investigated the potential impacts of bivalent and monovalent boosters, inspired by disease dynamics in low- and middle-income countries (LMICs). These models allowed us to test the role of natural immunity and cross-protection in determining optimal booster strategy. Our results show that in hypothetical populations with high pre-existing immunity in the 2022-23 season, disease-related deaths from a new variant would be more sensitive to boosting/no boosting than booster formulation (bivalent vs. monovalent) - and if using bivalent formulations would result in delayed implementation compared to monovalent, it would almost always be better to implement monovalent immediately. However, deaths might be more sensitive to bivalent formulations in populations with low pre-existing immunity. These findings suggest that for many places where acquiring new vaccine stock may be economically prohibitive, monovalent boosters could still have been implemented where pre-existing immunity was high. While this analysis focuses on policy concerns in 2022, these results remain relevant now amidst ongoing questions about optimal booster formulation and timing to combat emerging transmission waves of COVID-19.
- Reimagining the serocatalytic model for infectious diseases: a case study of common coronavirusesSoren L Larsen, Junke Yang, Huibin Lv, Yang Wei Huan, Qiwen Teo, Tossapol Pholcharee, Ruipeng Lei, Akshita B Gopal, Evan K Shao, Logan Talmage, and othersEpidemics, 2025
Despite the increased availability of serological data, understanding serodynamics remains challenging. Serocatalytic models, which describe the rate of seroconversion (gain of antibodies) and seroreversion (loss of antibodies) within a population, have traditionally been fit to cross-sectional serological data to capture long-term transmission dynamics. However, a key limitation is their binary assumption on serological status, ignoring heterogeneity in optical density levels, antibody titers, and/or exposure history. Here, we implemented Gaussian mixture models - an established statistical tool - to cross-sectional data in order to characterize serological diversity of seasonal human coronaviruses (sHCoVs) across a wide range of age groups. These methods consistently identified multiple distinct seropositive levels, suggesting that among seropositive individuals, the number of prior exposures or response to infection may vary. We fit adapted, multi-compartment serocatalytic models with different assumptions on exposure history and waning of antibodies. The best fit model for each sHCoV was always one that accounted for host variation in the scale of serological response to infection. These models allowed us to estimate the strength and frequency of serological responses, finding that the time for a seronegative individual to become seropositive ranges from 2.40 to 7.03 years across sHCoVs, and most individuals mount a strong antibody response reflected in high optical density values, skipping lower levels of seropositivity. We find that despite frequent infection and strong serological responses, for all sHCoVs except 229E, individuals are likely to become seronegative again at some point after their first infection. Nonetheless, our results also indicate that by age 22, for each sHCoV the probability of having seroconverted at least once is over 95%. Crucially, our reimagined serocatalytic methods can be flexibly adapted across pathogens, having the potential to be broadly applied beyond this work.
2024
- A systematic review of using population-level human mobility data to understand SARS-CoV-2 transmissionN Kostandova, C Schluth, R Arambepola, F Atuhaire, S Bérubé, T Chin, E Cleary, O Cortes-Azuero, B Garcı́a-Carreras, K H Grantz, M D T Hitchings, A T Huang, N Kishore, S Lai, S L Larsen, S Loisate, P Martinez, H R Meredith, R Purbey, T Ramiadantsoa, J Read, B L Rice, L Rosman, N Ruktanonchai, H Salje, K L Schaber, A J Tatem, J Wang, D A T Cummings, and A WesolowskiNature communications, 2024
The emergence of SARS-CoV-2 into a highly susceptible global population was primarily driven by human mobility-induced introduction events. Especially in the early stages, understanding mobility was vital to mitigating the pandemic prior to widespread vaccine availability. We conducted a systematic review of studies published from January 1, 2020, to May 9, 2021, that used population-level human mobility data to understand SARS-CoV-2 transmission. Of the 5505 papers with abstracts screened, 232 were included in the analysis. These papers focused on a range of specific questions but were dominated by analyses focusing on the USA and China. The majority included mobile phone data, followed by Google Community Mobility Reports, and few included any adjustments to account for potential biases in population sampling processes. There was no clear relationship between methods used to integrate mobility and SARS-CoV-2 data and goals of analysis. When considering papers focused only on the estimation of the effective reproductive number within the US, there was no clear relationship identified between this measure and changes in mobility patterns. Our findings underscore the need for standardized, systematic ways to identify the source of mobility data, select an appropriate approach to using it in analysis, and reporting.
2023
- Quantifying the impact of SARS-CoV-2 temporal vaccination trends and disparities on disease controlSoren L Larsen, Ikgyu Shin, Jefrin Joseph, Haylee West, Rafael Anorga, Gonzalo E Mena, Ayesha S Mahmud, and Pamela P MartinezScience Advances, 2023
SARS-CoV-2 vaccines have been distributed at unprecedented speed. Still, little is known about temporal vaccination trends, their association with socioeconomic inequality, and their consequences for disease control. Using data from 161 countries/territories and 58 states, we examined vaccination rates across high and low socioeconomic status (SES), showing that disparities in coverage exist at national and subnational levels. We also identified two distinct vaccination trends: a rapid initial rollout, quickly reaching a plateau, or sigmoidal and slow to begin. Informed by these patterns, we implemented an SES-stratified mechanistic model, finding profound differences in mortality and incidence across these two vaccination types. Timing of initial rollout affects disease outcomes more substantially than final coverage or degree of SES disparity. Unexpectedly, timing is not associated with wealth inequality or GDP per capita. While socioeconomic disparity should be addressed, accelerating initial rollout for all over focusing on increasing coverage is an accessible intervention that could minimize the burden of disease across socioeconomic groups. Speeding up vaccine rollout for all socioeconomic groups surpasses the impact of eliminating disparity or increasing coverage.
- Socioeconomically-inspired modeling to justify use of fine-grain mobility dataS.L. Larsen, W.E. Beyeler, E.C.S. Acquesta, K.A. Klise, and P.D. Finley2023
When designing measures to control infectious disease spread, it is crucial to understand the structure of the population for which interventions are being implemented. Recent work has highlighted the need for models that incorporate demographic heterogeneity not just in age structure but also by socioeconomic status (SES). Appropriately capturing additional sources of population heterogeneity requires considerable data and model development. To understand the potential disagreement between SES-explicit or SES-agnostic disease models, we adapted Sandia’s Adaptive Recovery Model (ARM) model to consider differences in contact structure and mortality by Social Vulnerability Index (SVI) on a theoretical network. We also incorporated an Average network that did not consider SVI. By exploring disparities in vaccine and PPE uptake by SES and comparing to Average networks, as well as analyzing the influence of global vs. local contact, we found that the two model constructions often predicted different outcomes. Whether these differences are truly reflective of incorporating SES, and which model most closely represents reality, merits further investigation.
- Disentangling the impact of natural infections and vaccination in a rapidly evolving pandemic: prioritizing limited vaccine supplies in low- and middle-income countriesS.L. Larsen, I. Noor, H. West, E. Chandra, P.P. Martinez, and A.N.M. KraayMeeting of the Advisory Committee on Immunization and Vaccines related Implementation Research, 2023