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In 2015, a Zika epidemic in Brazil began spreading throughout the Americas. Zika virus (ZIKV) entered Managua, Nicaragua, in January 2016 and caused an epidemic that peaked in July-September 2016. ZIKV seropositivity was estimated among participants of pediatric (n = 3,740) and household (n = 2,147) cohort studies, including an adult-only subset from the household cohort (n = 1,074), in Managua. Seropositivity was based on a highly sensitive and specific assay, the Zika NS1 blockade-of-binding ELISA, which can be used in dengue-endemic populations. Overall seropositivity for the pediatric (ages 2-14), household (ages 2-80), and adult (ages 15-80) cohorts was 36, 46, and 56%, respectively. Trend, risk factor, and contour mapping analyses demonstrated that ZIKV seroprevalence increased nonlinearly with age and that body surface area was statistically associated with increasing seroprevalence in children. ZIKV seropositivity was higher in females than in males across almost all ages, with adjusted prevalence ratios in children and adults of 1.11 (95% CI: 1.02-1.21) and 1.14 (95% CI: 1.01-1.28), respectively. No household-level risk factors were statistically significant in multivariate analyses. A spatial analysis revealed a 10-15% difference in the risk of ZIKV infections across our 3-km-wide study site, suggesting that ZIKV infection risk varies at small spatial scales. To our knowledge, this is the largest ZIKV seroprevalence study reported in the Americas, and the only one in Central America and in children to date. It reveals a high level of immunity against ZIKV in Managua as a result of the 2016 epidemic, making a second large Zika epidemic unlikely in the near future.

BackgroundInfluenza causes substantial morbidity and mortality worldwide, yet few data exist on influenza infection rates in tropical, developing countries. In 2011, we established the Nicaraguan Pediatric Influenza Cohort Study (NPICS) to study the burden and seasonality of influenza in Nicaraguan children. Here we describe the study design, methods, and participation data of the NPICS for 2011-2013.Methods/designA total of 1532 children aged 0 to 12 years were enrolled into the study in 2011, and an additional 401 children were enrolled between 2012 and 2013. Children were provided with all of their medical care through the study, and data on medical visits were recorded systematically. A number of surveys were conducted together with a blood sample annually, including a height and weight measurement, a socio-economic status and risk factor survey, and a breastfeeding survey.DiscussionUnique features of our study include the customized low-cost, open-source informatics system as well as the development of methods to leverage infrastructure and resources by conducting multiple studies in the same setting while maximizing protocol adherence and quality control. These methods should be useful to others conducting large cohort studies, particularly in low-resource settings.

BackgroundInfluenza causes substantial morbidity and mortality worldwide, yet few data exist on influenza infection rates in tropical, developing countries. In 2011, we established the Nicaraguan Pediatric Influenza Cohort Study (NPICS) to study the burden and seasonality of influenza in Nicaraguan children. Here we describe the study design, methods, and participation data of the NPICS for 2011-2013.Methods/designA total of 1532 children aged 0 to 12 years were enrolled into the study in 2011, and an additional 401 children were enrolled between 2012 and 2013. Children were provided with all of their medical care through the study, and data on medical visits were recorded systematically. A number of surveys were conducted together with a blood sample annually, including a height and weight measurement, a socio-economic status and risk factor survey, and a breastfeeding survey.DiscussionUnique features of our study include the customized low-cost, open-source informatics system as well as the development of methods to leverage infrastructure and resources by conducting multiple studies in the same setting while maximizing protocol adherence and quality control. These methods should be useful to others conducting large cohort studies, particularly in low-resource settings.