Estimating transmissibility of Zika virus in Colombia in the presence of surveillance bias

Tim K. Tsang (), Diana P. Rojas, Fei Xu, Yanfang Xu, Xiaolin Zhu, M. Elizabeth Halloran, Ira M. Longini and Yang Yang ()
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Tim K. Tsang: The University of Hong Kong
Diana P. Rojas: University of Florida
Fei Xu: The Hong Kong Polytechnic University
Yanfang Xu: The University of Hong Kong
Xiaolin Zhu: The Hong Kong Polytechnic University
M. Elizabeth Halloran: Fred Hutchinson Cancer Center
Ira M. Longini: University of Florida
Yang Yang: University of Florida

Nature Communications, 2025, vol. 16, issue 1, 1-9

Abstract: Abstract The 2015–2016 Zika virus outbreak in the Americas presented significant challenges in understanding the transmission dynamics due to substantial reporting biases, as women of reproductive age (15–39 years) were disproportionately represented in the surveillance data when public awareness of relationship between Zika and microcephaly increased. Using national surveillance data from Colombia during July 27, 2015–November 21, 2016, we developed a Bayesian hierarchical modeling framework to reconstruct the true numbers of symptomatic cases and estimate transmission parameters while accounting for differential reporting across age-sex groups. Our model revealed that the detection rate of symptomatic cases among women of reproductive age was 99% (95% CI: 98.7-100), compared to 85.4% (95% CI: 84.7-86.1) in other demographic groups. After correcting for these biases, our results showed that females aged 15–39 years remained 82.8% (95% CI: 80.2–85.2%) more susceptible to Zika symptomatic infection than males of the same age, independent of differential reporting areas. Departments with medium-high altitude, medium-high population density, low coverage of forest, or high dengue incidence from 2011–2015 exhibited greater Zika risk. This study underscores the importance of accounting for surveillance biases in epidemiological studies to better understand factors influencing Zika transmission and to inform disease control and prevention.

Date: 2025
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DOI: 10.1038/s41467-025-59655-9

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