Few studies of dengue have shown group-level associations between demographic, socioeconomic, or geographic characteristics and the spatial distribution of dengue within small urban areas. This study aimed to examine whether specific characteristics of an urban slum community were associated with the risk of dengue disease. From 01/2009 to 12/2010, we conducted enhanced, community-based surveillance in the only public emergency unit in a slum in Salvador, Brazil to identify acute febrile illness (AFI) patients with laboratory evidence of dengue infection. Patient households were geocoded within census tracts (CTs). Demographic, socioeconomic, and geographical data were obtained from the 2010 national census. Associations between CTs characteristics and the spatial risk of both dengue and non-dengue AFI were assessed by Poisson log-normal and conditional auto-regressive models (CAR). We identified 651 (22.0%) dengue cases among 2,962 AFI patients. Estimated risk of symptomatic dengue was 21.3 and 70.2 cases per 10,000 inhabitants in 2009 and 2010, respectively. All the four dengue serotypes were identified, but DENV2 predominated (DENV1: 8.1%; DENV2: 90.7%; DENV3: 0.4%; DENV4: 0.8%). Multivariable CAR regression analysis showed increased dengue risk in CTs with poorer inhabitants (RR: 1.02 for each percent increase in the frequency of families earning ≤1 times the minimum wage; 95% CI: 1.01-1.04), and decreased risk in CTs located farther from the health unit (RR: 0.87 for each 100 meter increase; 95% CI: 0.80-0.94). The same CTs characteristics were also associated with non-dengue AFI risk. This study highlights the large burden of symptomatic dengue on individuals living in urban slums in Brazil. Lower neighborhood socioeconomic status was independently associated with increased risk of dengue, indicating that within slum communities with high levels of absolute poverty, factors associated with the social gradient influence dengue transmission. In addition, poor geographic access to health services may be a barrier to identifying both dengue and non-dengue AFI cases. Therefore, further spatial studies should account for this potential source of bias. Dengue is influenced by the environment; however, few studies have investigated the relationship between neighborhood characteristics and the spatial distribution of dengue within small urban areas. We examined whether specific characteristics of an urban slum community were associated with dengue risk. From January 2009 to December 2010, we conducted community-based surveillance in a slum in Salvador, Brazil to identify patients with acute febrile illness (AFI) and to test them for dengue. We identified 651 (22.0%) patients with laboratory evidence of dengue infection among 2,962 AFI patients. All the four dengue serotypes were detected, but DENV2 predominated (DENV1 8.1%; DENV2 90.7%; DENV3 0.4%; DENV4 0.8%). Estimated risk of symptomatic dengue was 21.3 and 70.2 cases per 10,000 inhabitants in 2009 and 2010, respectively. We found that neighborhood poverty level and proximity to the health center were associated with higher risk of detection of dengue and other AFI. This study highlights the large burden of dengue in poor urban slums of Brazil and indicates that socioeconomic development could potentially mitigate risk factors for both dengue and non-dengue AFI cases. In addition, we found that residential proximity to a health care facility was associated with improved case detection. Therefore, further studies on disease distribution should consider household proximity to health care facilities when assessing risk.

Since their emergence in the Americas, chikungunya (CHIKV) and Zika (ZIKV) viruses co-circulate with dengue virus (DENV), hampering clinical diagnosis. We investigated clinical and epidemiological characteristics of arboviral infections during the introduction and spread of CHIKV and ZIKV through northeastern Brazil. Surveillance for arboviral diseases among febrile patients was performed at an emergency health unit of Salvador, Brazil, between September 2014 and July 2016. We interviewed patients to collect data on symptoms, reviewed medical records to obtain the presumptive diagnoses, and performed molecular and serological testing to confirm DENV, CHIKV, ZIKV, or nonspecific flavivirus (FLAV) diagnosis. Of 948 participants, 247 (26.1%) had an acute infection, of which 224 (23.6%) were single infections (DENV, 32 [3.4%]; CHIKV, 159 [16.7%]; ZIKV, 13 [1.4%]; and FLAV, 20 [2.1%]) and 23 (2.4%) coinfections (DENV/CHIKV, 13 [1.4%]; CHIKV/FLAV, 9 [0.9%]; and DENV/ZIKV, 1 [0.1%]). An additional 133 (14.0%) patients had serological evidence for a recent arboviral infection. Patients with ZIKV presented with rash and pruritus (69.2% each) more frequently than those with DENV (37.5% and 31.2%, respectively) and CHIKV (22.9% and 14.7%, respectively) (P < .001 for both comparisons). Conversely, arthralgia was more common in CHIKV (94.9%) and FLAV/CHIKV (100.0%) than in DENV (59.4%) and ZIKV (53.8%) (P < .001). A correct presumptive clinical diagnosis was made for 9%–23% of the confirmed patients. Arboviral infections are frequent causes of febrile illness. Coinfections are not rare events during periods of intense, concomitant arboviral transmission. Given the challenge to clinically distinguish these infections, there is an urgent need for rapid, point-of-care, multiplex diagnostics.

Zika virus infection emerged as a public health emergency after increasing evidence for its association with neurologic disorders and congenital malformations. In Salvador, Brazil, outbreaks of acute exanthematous illness (AEI) attributed to Zika virus, Guillain-Barré syndrome (GBS), and microcephaly occurred in 2015. We investigated temporal correlations and time lags between these outbreaks to identify a common link between them by using epidemic curves and time series cross-correlations. Number of GBS cases peaked after a lag of 5–9 weeks from the AEI peak. Number of suspected cases of microcephaly peaked after a lag of 30–33 weeks from the AEI peak, which corresponded to time of potential infections of pregnant mothers during the first trimester. These findings support the association of GBS and microcephaly with Zika virus infection and provide evidence for a temporal relationship between timing of arboviral infection of pregnant women during the first trimester and birth outcome.