Repeated Rapid Active Sampling Surveys Demonstrated a Rapidly Changing Zika Seroprevalence among Children in a Rural Dengue-endemic Region in Southwest Guatemala during the Zika Epidemic (2015-2016).

Although Central America is largely dengue virus (DENV)-endemic, the 2015-2016 Zika virus (ZIKV) pandemic brought new urgency to develop surveillance approaches capable of characterizing the rapidly changing disease burden in resource-limited settings. We conducted a pediatric DENV surveillance study in rural Guatemala, including serial cross-sectional surveys from April through September 2015 (Survey 1), in October-November 2015 (Survey 2), and January-February 2016 (Survey 3). Serum underwent DENV IgM MAC ELISA and polymerase chain reaction testing. Using banked specimens from Surveys 2 and 3, we expanded testing to include DENV 1-4 and ZIKV microneutralization (MN50), DENV NS1 IgG ELISA, and ZIKV anti-NS1 antibody Blockage of Binding (BoB) ELISA testing. Demographic risk factors for ZIKV BoB positivity were explored using multivariable generalized linear regression models. Of Survey 2 and 3 samples available (N = 382), DENV seroprevalence slightly increased (+1%-10% depending on the assay) during the surveillance period and increased with age. In contrast, ZIKV seroprevalence consistently increased over the 3-month period, including from 6% to 34% (P < 0.0001) and 10%-37% (P < 0.0001) using the MN50 ≥100 and BoB ELISA assays, respectively. Independent risk factors for ZIKV seropositivity included older age (prevalence ratio (PR)/year = 1.12, 95% confidence interval (CI) = 1.07-1.17) and primary caregiver literacy (PR = 2.80, CI = 1.30-6.06). Rapid active surveillance (RAS) surveys demonstrated a nearly 30% increase in ZIKV prevalence and a slight (≤ 10%) increase in DENV seroprevalence from October to November 2015 to January to February 2016 in rural southwest Guatemala, regardless of serologic assay used. RAS surveys may be a useful "off-the-shelf" tool to characterize arboviruses and other emerging pathogens rapidly in resource-limited settings.