Zika emergence, persistence, and transmission rate in Colombia: a nationwide application of a space-time Markov switching model

Abstract

Zika, a viral disease transmitted to humans by Aedes mosquitoes, emerged in the Americas in 2015, causing large-scale epidemics. Colombia alone reported over 72,000 Zika cases between 2015 and 2016. Using national surveillance data from 1121 municipalities over 70 weeks, we identified sociodemographic and environmental factors associated with Zika's emergence, re-emergence, persistence, and transmission intensity in Colombia. We fitted a zero-state Markov-switching model under the Bayesian framework, assuming Zika switched between periods of presence and absence according to spatially and temporally varying probabilities of emergence/re-emergence (from absence to presence) and persistence (from presence to presence). These probabilities were assumed to follow a series of mixed multiple logistic regressions. When Zika was present, assuming that the cases follow a negative binomial distribution, we estimated the transmission intensity rate. Our results indicate that Zika emerged/re-emerged sooner and that transmission was intensified in municipalities that were more densely populated, at lower altitudes and/or with less vegetation cover. Warmer temperatures and less weekly-accumulated rain were also associated with Zika emergence. Zika cases persisted for longer in more densely populated areas with more cases reported in the previous week. Overall, population density, elevation, and temperature were identified as the main contributors to the first Zika epidemic in Colombia. We also estimated the probability of Zika presence by municipality and week, and the results suggest that the disease circulated undetected by the surveillance system on many occasions. Our results offer insights into priority areas for public health interventions against emerging and re-emerging Aedes-borne diseases.

Figure 1

Examples of different temporal patterns of Zika reported cases counts by epidemiological week of first symptoms in selected municipalities of Colombia, epidemiological weeks 22/2015 to 39/2016: (A) disease observed always absent in Bolívar (above 1800m of altitude and average temperature of 20 ^∘C); (B) few cases reported intermittently in Marmato (above 1300m, 22 ^∘C); (C) an observed emergence with very few cases followed by observed extinction and observed re-emergence with more cases being reported in San Martín (below 500m, 27 ^∘C); (D) an early emergence followed by observed extinction and subsequent re-emergence in El Zulia (below 200m, 27 ^∘C); (E) few and sporadic cases being reported in Guarne (above 2000m, 18 ^∘C); and (F) an observed emergence followed by observed extinction in Campoalegre (around 500m, 24 ^∘C). Data source: Colombian National Public Health Surveillance System—Sistema Nacional de Vigilancia en Salud Pública (SIVIGILA).

Figure 2

Diagram presenting the basic model structure considering three disease states: initial absence, presence, and subsequent absence.

Figure 3

Localization of Colombia in the Americas and map of Colombia with the municipalities and geographical departments limits and the cumulative incidence of reported Zika cases per 10,000 inhabitants by municipality of residence from epidemiological weeks 22/2015 to 39/2016. Map created using QGIS (version 3.22) (QGIS.org, 2021. QGIS Geographic Information System. QGIS Association. http://www.qgis.org). Sources: Colombian National Administrative Department of Statistics—DANE—geoportal. Colombian National Public Health Surveillance System - SIVIGILA. Background map tiles by Stamen Design, under CC BY 3.0. Data by OpenStreetMap, under ODbL.

Figure 4

Association of covariates with the Zika epidemic in Colombia, epidemiological weeks 22/2015 to 39/2016. (A) Posterior distribution of the rate ratio/odds ratio associated with standardized covariates* and the transmission intensity rate, probabilities of emergence and re-emergence, and probability of persistence of Zika, and (B) posterior mean of the transmission intensity rate, probability of emergence, re-emergence, and persistence of Zika by department after adjusting for the department-specific random effect and the average values of the covariates in the department. Maps created using R (version 4.3.2, https://www.r-project.org/). *Population density and cases_t-1 are log transformed. UBN = percentage of the population with unsatisfied basic needs. NDVI = Normalized Difference Vegetation Index.

Figure 5

Fitting of the number of Zika cases and posterior probability of each disease state by epidemiological week (EW) in three selected municipalities, EWs 22/2015 to 39/2016, Colombia. (A) Observed versus fitted number of Zika cases (mean and 95% Credible Interval—CI) and (B) posterior probability of initial absence, presence, and subsequent absence of Zika.

Figure 6

Posterior probability of Zika presence (first row) and observed number of reported Zika cases (second row) by municipality in four moments of time between epidemiological weeks (EWs) 22/2015 and 39/2016, Colombia. Maps created using R (version 4.3.2, https://www.r-project.org/).