Behavioral, climatic, and environmental risk factors for Zika and Chikungunya virus infections in Rio de Janeiro, Brazil, 2015-16

<div><p>The burden of arboviruses in the Americas is high and may result in long-term sequelae with infants disabled by Zika virus infection (ZIKV) and arthritis caused by infection with Chikungunya virus (CHIKV). We aimed to identify environmental drivers of arbovirus epidemics to predict where the next epidemics will occur and prioritize municipalities for vector control and eventual vaccination. We screened sera and urine samples (<i>n</i> = 10,459) from residents of 48 municipalities in the state of Rio de Janeiro for CHIKV, dengue virus (DENV), and ZIKV by molecular PCR diagnostics. Further, we assessed the spatial pattern of arbovirus incidence at the municipal and neighborhood scales and the timing of epidemics and major rainfall events. Lab-confirmed cases included 1,717 infections with ZIKV (43.8%) and 2,170 with CHIKV (55.4%) and only 29 (<1%) with DENV. ZIKV incidence was greater in neighborhoods with little access to municipal water infrastructure (<i>r</i> = -0.47, <i>p</i> = 1.2x10^-8). CHIKV incidence was weakly correlated with urbanization (<i>r</i> = 0.2, <i>p</i> = 0.02). Rains began in October 2015 and were followed one month later by the largest wave of ZIKV epidemic. ZIKV cases markedly declined in February 2016, which coincided with the start of a CHIKV outbreak. Rainfall predicted ZIKV and CHIKV with a lead time of 3 weeks each time. The association between rainfall and epidemics reflects vector ecology as the larval stages of <i>Aedes aegypti</i> require pools of water to develop. The temporal dynamics of ZIKV and CHIKV may be explained by the shorter incubation period of the viruses in the mosquito vector; 2 days for CHIKV versus 10 days for ZIKV.</p></div

Characteristics of the LABFLA data set.

<p>ZIKV samples were collected from January 2015 to May 2016, and CHIKV from September 2015 to October 2016.</p

Cases of CHIKV and ZIKV by age among the LABFLA lab-confirmed positives.

<p>Cases of CHIKV and ZIKV by age among the LABFLA lab-confirmed positives.</p

Model in which CHIKV outcompetes ZIKV is supported by the data.

<p>In the observed epidemiological data (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0188002#pone.0188002.g002" target="_blank">Fig 2</a>), the epidemic of ZIKV occurred before that of CHIKV. In our simulations, CHIKV spread more quickly than ZIKV in the mosquito, and the outbreak of ZIKV was followed by an outbreak of CHIKV.</p

Confirmed cases of ZIKV and CHIKV per week in the state of Rio de Janeiro, March 2015 to May 2016 (LABFLA data set).

<p>Confirmed cases of ZIKV and CHIKV per week in the state of Rio de Janeiro, March 2015 to May 2016 (LABFLA data set).</p

Effect of infrastructure on CHIKV and ZIKV incidence in the city of Rio de Janeiro.

<p>Each point represents one neighborhood in the city of Rio de Janeiro. Incidence was defined as the number of lab-confirmed cases per 10,000 inhabitants. (A) ZIKV incidence is greater in neighborhoods with little access to municipal water supplies in the city of Rio de Janeiro. (B) CHIKV incidence increases with the percentage of urbanized land in the neighborhood.</p

Geographic pattern of ZIKV and CHIKV incidence.

<p>(A) High correlation between the incidence of ZIKV and CHIKV in the Metro 2 health region, which comprises the eastern half of the metropolitan area of the city of Rio de Janeiro. This geographic overlap between the viruses could have led to competition in <i>Aedes aegypti</i>. The correlation is moderate but lower in the Metro 1 region. The Metro 1 and 2 regions represent 80% of the state’s population and 90% of the samples in this analysis. The correlation is also high in the North and Coastal regions, whereas in other health regions, ZIKV and CHIKV appear not to be correlated. However, the lower sample sizes outside the metropolitan area make it difficult to draw robust conclusions about the correlation in these regions. (B) Relative proportion of ZIKV and CHIKV. ZIKV dominates over CHIKV in the Rio de Janeiro metropolitan area and the Coastal and North health regions. (C) Human population density.</p

Compartmental model used to simulate CHIKV and ZIKV epidemics.

<p>Compartmental model used to simulate CHIKV and ZIKV epidemics.</p