BackgroundFew 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.Methodology/Principal FindingsFrom 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.Conclusions/SignificanceThis 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.

No abstract

No abstract

On April 2, 2015, four patients were evaluated at the University of Mississippi Medical Center (UMMC) in Jackson, Mississippi, for agitated delirium after using synthetic cannabinoids. Over the next 3 days, 24 additional persons went to UMMC with illnesses suspected to be related to synthetic cannabinoid use; one patient died. UMMC notified the Mississippi State Department of Health, which issued a statewide alert via the Health Alert Network on April 5, requesting that health care providers report suspected cases of synthetic cannabinoid intoxication to the Mississippi Poison Control Center (MPCC). A suspected case was defined as the occurrence of at least two of the following symptoms: sweating, severe agitation, or psychosis in a person with known or suspected synthetic cannabinoid use. A second statewide alert was issued on April 13, instructing all Mississippi emergency departments to submit line lists of suspected patients to MPCC each day. By April 21, 16 days after the first alert was issued, MPCC had received reports of approximately 400 cases, including eight deaths possibly linked to synthetic cannabinoid use; in contrast, during April 2012–March 2015, the median number of telephone calls to MPCC regarding synthetic cannabinoid use was one per month (range = 0–11). The Mississippi State Department of Health, with the assistance of CDC, initiated an investigation to better characterize the outbreak, identify risk factors associated with severe illness, and prevent additional illnesses and deaths.

SC use can cause severe health effects. MAB-CHMINACA was the most commonly detected SC in this outbreak. As new SCs are created, new strategies to optimize surveillance and patient care are needed to address this evolving public health threat.