Stratifying the potential local transmission of Zika in municipalities of Antioquia, Colombia. Issue 10 (5th September 2017)

• Record Type: Journal Article
• Authors: Ospina, Juan; Hincapie‐Palacio, Doracelly; Ochoa, Jesús; Molina, Adriana; Rúa, Guillermo; Pájaro, Dubán; Arrubla, Marcela; Almanza, Rita; Paredes, Marlio; Mubayi, Anuj
• Is Part Of: Tropical medicine & international health. Volume 22:Issue 10(2017)
• Page Start: 1249
• Page End: 1265
• Publication Date: 2017-09-05
• Subjects: Zika -- basic reproductive number -- mathematical model -- Colombia; Zika -- nombre de reproduction de base -- modèle mathématique -- Colombie; Zika -- número reproductivo básico -- modelo matemático -- Colombia; Tropical medicine -- Periodicals; Public health -- Periodicals; 616.988
• DOI: 10.1111/tmi.12924
• Languages: English
• ISSNs: 1360-2276

Abstract

Abstract: Objective: To stratify and understand the potential transmission processes of Zika virus in Colombia, in order to effectively address the efforts on surveillance and disease control. Methods: We compare R 0 of Zika for municipalities based on data from the regional surveillance system of Antioquia, Colombia. The basic reproduction number ( R 0 ) and its 95% confidence intervals were estimated from an SIR model with implicit vector dynamics, in terms of recovered individuals in each time unit, using an approximate solution. These parameters were estimated fitting the solution of the model to the daily cumulative frequency of each Zika case according to symptoms onset date relative to the index case reported to the local surveillance system. Results: R 0 was estimated for 20 municipalities with a median of 30 000 inhabitants, all located less than 2200 m above sea level. The reported cases ranged from 17 to 347 between these municipalities within 4 months (January to April of 2016). The results suggest that 15 municipalities had a high transmission potential ( R 0 > 1), whereas in five municipality transmissions were potentially not sustaining ( R 0 < 1), although the upper bound of the confidence interval of the R 0 for 3 of these 5 was greater than one, indicating the possibility of an outbreak later on. Conclusion: The study identified high‐risk municipalities ( R 0 > 1) and provide a technique to optimise surveillance and control of Zika. Health authorities should promote the collection, analysis, modelling and sharing of anonymous data onto individual cases to estimate R 0 .