Local heterogeneity in Lassa fever serology in rural Nigeria: Implications for vaccine trial site selection

Figures Abstract Introduction Lassa virus (LASV) causes significant morbidity in West Africa, yet vaccine trial planning is hampered by a lack of high-resolution, community-level seroprevalence data. We aimed to characterize the fine-scale spatial and demographic heterogeneity of LASV exposure in rural Nigeria to inform site selection strategies. Methods We conducted a cross-sectional serosurvey across nine villages in three Nigerian states (Benue, Ebonyi, and Cross River). We recruited 1,874 individuals and tested for LASV IgG using the highly specific Panadea LASV IgG ELISA. We employed Bayesian hierarchical models to estimate seroprevalence and investigated 21 pre-specified demographic, environmental, and behavioral risk factors for association with seropositivity. Village-specific transmission dynamics were explored using Bayesian generalized additive models for age-stratified seroprevalence. Results The overall model-based IgG seroprevalence was 3.2% (95% CrI: 2.5–4.0%). We observed marked fine-scale heterogeneity, with village-level estimates ranging from 0.8% to 6.5%. Age-seroprevalence curves suggested? divergent transmission dynamics, ranging from cumulative endemic exposure to recent focal outbreaks in younger cohorts. Likely constrained by low overall prevalence and high exposure ubiquity, univariable analyses detected no strong or consistent associations between seropositivity and the 21 pre-specified risk factors, including rodent consumption and agricultural practices. No significant village-wide spatial clustering of seropositive households was observed via Local Getis-Ord (Gi*). Discussion LASV exposure in rural Nigeria is characterized by low overall prevalence punctuated by significant hyper-local variation. The lack of consistent individual-level risk factors and the divergent age-exposure profiles suggest that risk may be influenced by stochastic, localized ecological drivers or obscured by the temporal misalignment of cross-sectional surveys. Vaccine trial site selection must move beyond regional incidence data to incorporate interdisciplinary, One Health metrics including high-resolution human serosurveillance and longitudinal reservoir monitoring to identify active transmission hotspots. Author summary Why was this study done? Lassa fever is a significant viral disease in West Africa, and several vaccine candidates are currently in development. To evaluate vaccine efficacy in Phase III clinical trials, researchers must identify communities with active, ongoing viral transmission. However, Lassa virus spillover is highly unpredictable, making it difficult to select trial sites based on regional maps or passive clinical reporting. We aimed to determine if current broad-scale risk models accurately reflect local exposure and to identify the specific drivers of infection at the community level. What did the researchers do and find? We tested 1,874 individuals across nine rural villages in Nigeria for Lassa virus IgG antibodies. We found that infection rates were generally low (overall 3.2%) but exhibited significant fine-scale variation: seroprevalence ranged from less than 1% to over 6% between villages, even those in close proximity. We investigated 21 potential risk factors, including rodent consumption, agricultural practices, and household environment, but – likely constrained by the low overall infection rate - found no consistent associations with infection. Furthermore, the patterns of infection by age differed between villages, suggesting communities may experience differing transmission dynamics, ranging from stable, long-term exposure to more episodic transmission. What do these findings mean? Our results show that Lassa virus risk is hyper-local and cannot be reliably predicted by broad regional maps or human behavior alone. This suggests that infection risk may be influenced by stochastic, local ecological factors, such as the fluctuating presence of the virus within specific rodent populations. For vaccine trials, this means that relying on regional incidence data may lead to selecting sites with insufficient transmission to measure vaccine success. We suggest that trial planning must adopt a One Health design integrating active human serosurveillance with longitudinal monitoring of rodent reservoirs to accurately identify active transmission hotspots for successful vaccine testing. Citation: Simons D, Harden C, Imirzian N, Thompson KET, Ifebueme NM, Eziechina S, et al. (2026) Local heterogeneity in Lassa fever serology in rural Nigeria: Implications for vaccine trial site selection. PLoS Negl Trop Dis 20(5): e0014379. https://doi.org/10.1371/journal.pntd.0014379 Editor: David Safronetz, Public Health Agency of Canada, CANADA Received: January 21, 2026; Accepted: May 14, 2026; Published: May 21, 2026 Copyright: © 2026 Simons et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: Zenodo provides the permanent Digital Object Identifier (DOI) for the specific release of the code and data used in this manuscript. As GitHub repositories are not permanent archives, retaining the Zenodo DOI is essential for long-term reproducibility and compliance with standard open science practices. Therefore, please typeset the statement as follows: “All de-identified data and associated R scripts required to reproduce these analyses are available on GitHub (https://github.com/RiskLabPSU/baseline-seroprev-public) and permanently archived on Zenodo (https://doi.org/10.5281/zenodo.19677372). Funding: This work was supported by the joint National Science Foundation?National Institutes of Health?National Institutes of Food and Agriculture Ecology and Evolution of Infectious Disease Award (Grant #2208034 to SF) and the United Kingdom Research and Innovation Biotechnology and Biological Sciences Research Council (Grant BB/X005364/1 to DWR). DS, NI, KETT, NMI, HOI, DM, and JTK received salary support from these grants. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist. Introduction Lassa virus (Mammarenavirus lassaense; Arenaviridae, LASV) is a zoonotic arenavirus endemic to West Africa, with regular outbreaks occurring in Nigeria, Guinea, Liberia, and Sierra Leone. It causes Lassa fever, a viral hemorrhagic illness responsible for an estimated 900,000 annual infections and over 200 deaths annually in Nigeria alone [1]. Clinical presentation ranges from asymptomatic infection to severe hemorrhagic fever with case fatality exceeding 20% in hospitalized patients, for whom treatment options remain limited [2]. The primary reservoir for LASV is Mastomys natalensis, a highly fecund, synanthropic rodent widely distributed across sub-Saharan Africa [3]. It thrives in agricultural and peri-domestic environments, creating substantial opportunities for human contact [4]. Infected rodents, particularly those infected vertically in utero, can become persistent shedders of the virus in excreta, while its fluctuating population dynamics influence seasonal transmission intensity [5,6]. Human infection occurs primarily through direct or indirect contact with infected rodents, their excreta, contaminated food, or aerosolized particles [7]. Occupational and domestic exposures, particularly in farming, food storage, and rodent hunting contexts, are commonly implicated. However, the relative contribution of these pathways remains debated, and seroprevalence surveys show that exposure is widespread yet highly variable, with most infections (~80%) being asymptomatic or subclinical, meaning case counts severely underestimate the true infection burden [8,9]. Environmental and ecological conditions strongly influence LASV spillover [10]. Land use changes like deforestation and agricultural intensification can increase human-rodent contact, while shifts in rodent community composition may also moderate risk [11–13]. Despite these broad-scale drivers, observed variation in LASV prevalence between ecologically similar areas highlights the critical importance of fine-scale factors [14]. These include social conditions, such as household structure, food storage methods, and specific human-animal interactions. Understanding this fine-scale variation is not solely academic but is a prerequisite for the successful deployment of future medical countermeasures LASV is a designated priority pathogen for the World Health Organization and the Coalition for Epidemic Preparedness Innovations (CEPI), with multiple vaccine candidates currently advancing into clinical trials [15]. The success of future Phase III efficacy trials relies on identifying communities where incidence is sufficient to measure a vaccine effect. However, relying on broad-scale incidence data or passive surveillance to select these sites risks recruitment failure if transmission is more focal than regional risk maps suggest, resulting in prolonged timelines for case accrual sufficient to demonstrate vaccine efficacy [16]. Current Lassa fever surveillance relies primarily on passive case detection at sentinel hospitals, which overlooks mild infections and asymptomatic seroconversion in the community [17]. As a result, major gaps remain in our understanding of the null areas and regions that appear ecologically suitable but report few cases. To address this, we conducted a cross-sectional study in nine communities across three Nigerian states [18]. We combined serological testing with structured questionnaires to investigate fine-scale drivers of exposure. Our objectives were to: 1) estimate LASV seroprevalence at state and village levels; 2) characterize individual and household correlates of seropositivity; and 3) explore spatial heterogeneity in local transmission risk. Materials and methods The primary objective of this study was to estimate the seroprevalence of LASV IgG in nine communities across three Nigerian states. Secondary objectives were to explore demographic, environmental, behavioral, and occupational correlates of seropositivity and to assess fine-scale spatial heterogeneity of exposure. Ethics statement The study protocol was approved by the Institutional Review Board of the Pennsylvania State University, USA (STUDY00019989), and by the Nigerian National Health Research Ethics Committee (AEC/03/168/24). Additional approval was obtained from the health research ethics committees of the public health agencies in each participating state. The study was conducted in accordance with the Declaration of Helsinki. Enrolment involved engagement with community leaders. Written informed consent was obtained from all adults; assent and written parental consent were obtained for minors. Study design and participants This cross-sectional baseline survey was conducted as part of the SCAPES longitudinal study [18]. Nine villages across three states (Benue [BN], Ebonyi [EB], and Cross River [CR]) were selected using a systematic framework designed to sample communities across a gradient of postulated drivers of LASV spillover [19]. These states were chosen to represent a range of environmental suitability as defined by national-scale mechanistic modelling, which categorized them into high, medium, and low-risk tiers [20]. Using the site selection tool [19], candidate settlements were identified via OpenStreetMap. Land cover characteristics (ESA WorldCover) were analyzed within a 2-km radius representing the home range of the reservoir species (M. natalensis) to ensure sites reflected rural agricultural areas. We specifically targeted medium-sized villages (100–500 households) and excluded sites with >60% forest cover or >20% built-up area. Final site selection was validated to ensure no systematic bias relative to other settlements in the region and to ensure the sampled villages appropriately reflected the local variation in cropland and grassland proportions. This approach was designed to represent a spectrum of LASV spillover risk across the three states, rather than targeting known hotspot communities, thereby providing a more representative baseline of regional seroprevalence. To contextualize our findings within the national epidemiological landscape, we collated historical passive surveillance data from the Nigeria Centre for Disease Control (NCDC) [21]. Specifically, we extracted the number of years each corresponding Local Government Area (LGA) had reported confirmed Lassa fever cases prior to the survey [22]. Households were enumerated to estimate population size and plan recruitment. Villages ranged from 110 to 321 households (population 465–2,313; S1 Fig). To prevent demographic sampling bias (such as over-representing individuals who remain at home during the day), we employed a strict intra-household quota system. We aimed to recruit ~20% of households per village (target ~70), specifically enrolling exactly four individuals per household: one adult male, one adult female, one adolescent (12–18), and one randomly selected child (40% seroprevalence), medium-risk (10–20%), and low-risk (0.1; this ensured the identified variation was of a meaningful magnitude rather than a statistical artefact of the regularizing prior [33]. Estimating LASV seroprevalence We estimated seroprevalence and 95% CrIs using Bayesian generalized linear mixed models (GLMM) with a binary outcome (seropositive/seronegative) and a single fixed effect for state or village. Posterior predictions generated marginal estimates averaged over sampled individuals. To explore age-related variation, we fitted a Bayesian generalized additive model (GAM) with village-specific smooth terms for age. Posterior expected probabilities were calculated across a grid of age values to obtain modelled estimates. The full posterior summaries (central estimates and CrIs) for these models are presented in S2 and S3 Tables. Differences classed as important are indicated in the main text and tables. We utilized weakly informative priors for all fixed effects (Normal(0, 5)) and random effects (Exponential(1)) to allow the data to drive inference while stabilizing computation in low-prevalence groups. We did not attempt to formally estimate the Force of Infection (FOI) using catalytic models. Such models typically assume a time-invariant infection hazard, which we deemed inappropriate given the evidence of stochastic, episodic transmission in this region. Furthermore, the low number of seropositive cases (N = 61) across a wide age range precluded the stable estimation of a time-varying FOI model, which would require substantially higher power to distinguish between age-dependent risk and historical fluctuations in viral circulation. Characterizing behavioral and ex