High-resolution spatiotemporal analysis of chikungunya epidemics between 2019 and 2020 in Salvador, Brazil: a municipality-level transmission dynamics study

Abstract

Background

Chikungunya virus (CHIKV) continues to cause explosive epidemics in Brazil. We investigated its transmission dynamics in Salvador, Brazil, to understand the factors driving its reemergence and spread.

Methods

In this epidemiological study, we analyzed by census tracts the chikungunya cases reported in Salvador during the 2019–2020 epidemics. We used SaTScan software to identify spatiotemporal clusters and assessed how census tract characteristics (socioeconomic, environmental, and prior chikungunya occurrence) influenced chikungunya incidence through a Bayesian spatial model using Integrated Laplace Approximation (INLA).

Findings

Citywide, 19,129 cases (mean age: 40.2, range: 0–112; male: 41.8%, female: 58.0%, non-binary: 0.2%) were reported between 2016 and 2020, with a significant increase in 2019 and 2020 (4549 and 13,071 cases, respectively). We found nine spatiotemporal clusters in 2019 and seven in 2020, with 17.2% (387 of 2252) overlap of census tracts between the two years. The chikungunya incidence by census tract was negatively correlated with income and vegetation but positively correlated with land surface temperature. The census tract level incidence in 2020 exhibited a non-linear correlation with the 2019 incidence; up to a certain level, the 2020 risk increased as the 2019 incidence increased, but when the 2019 incidence was extreme, the 2020 risk was reduced.

Interpretation

These findings suggest that CHIKV transmission is localized, even during what appeared to be a citywide epidemic, creating high-risk pockets within the city. Socioeconomic factors, environmental conditions, and prior chikungunya incidence, probably reflecting herd immunity, all influence case incidence.

Funding

Secretary of Health of Salvador, Federal University of Bahia, Oswaldo Cruz Foundation, National Council for Scientific and Technological Development, Foundation for Research Support of the Bahia State, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES), Clinical and Applied Research Network in Chikungunya, Global Virus Network, Burroughs Wellcome Fund, Wellcome Trust, and the United States National Institutes of Health.