Epidemiology, Temporal and Seasonal Trends, and Geographic Distribution of Leptospirosis in the Dominican Republic, 2012 to 2026

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

This article is not in any list yet, why not save it to one of your lists.
Log in to save this article

Abstract

Leptospirosis is a widespread zoonotic infection and a growing public health concern in tropical, resource-limited settings, yet remains underrecognized and underreported where diagnostic and surveillance infrastructure is limited. We conducted an analytical cross-sectional study of national surveillance data from the Dominican Republic (2012-June 2026), integrating geospatial meteorological data to characterize disease burden, trends, seasonality, and clinical risk factors. Of 8,425 records, 5,412 met case-definition criteria (3,441 suspected, 1,448 probable, 523 confirmed), yielding a cumulative incidence of 3.55 per 100,000 person-years (2012-2025). Laboratory confirmation rose markedly, from 9.7% overall to half of 2025 cases and over half in 2026. Overall incidence remained stable across all years (p = 0.15), though with three distinct periods: declining infection pre-COVID, low infection during COVID, and increasing infection post-COVID. Cases clustered in the rainy/hurricane season (61.1%, May-November; p< 0.001), with a marginal rainfall correlation (r= 0.553, p= 0.062). Rural provinces bore disproportionate risk, led by Hermanas Mirabal (16.43/100,000 person-years), while large urban and coastal provinces had rates 80% lower. Men had 2.73-fold higher incidence than women (95% CI 2.56-2.90), peaking at younger ages 10-29. Comorbidity was the strongest predictor of complications (OR 2.84, 95% CI 2.01-4.02, p< 0.001). Limited diagnostic confirmation remains the central obstacle to characterizing leptospirosis burden in the Dominican Republic, with confirmation rates exceeding 40% only from 2023 onward. This first multi-decade national analysis identifies high-risk provinces, demographic groups, and seasonal windows for targeted surveillance, highlighting expanded diagnostic capacity as a priority for burden estimation and case management.

Article activity feed