Fine-scale heterogeneity in population density predicts wave dynamics in dengue epidemics.

The spread of dengue and other arboviruses constitutes an expanding global health threat. The extensive heterogeneity in population distribution and potential complexity of movement in megacities of low and middle-income countries challenges predictive modeling, even as its importance to disease spread is clearer than ever. Using surveillance data at fine resolution from Rio de Janeiro, we document a scale-invariant pattern in the size of successive epidemics following DENV4 emergence. Using surveillance data at fine resolution following the emergence of the DENV4 dengue serotype in Rio de Janeiro, we document a pattern in the size of successive epidemics that is invariant to the scale of spatial aggregation. This pattern emerges from the combined effect of herd immunity and seasonal transmission, and is strongly driven by variation in population density at sub-kilometer scales. It is apparent only when the landscape is stratified by population density and not by spatial proximity as has been common practice. Models that exploit this emergent simplicity should afford improved predictions of the local size of successive epidemic waves.

Time series analysis of dengue surveillance data in two Brazilian cities.

The aim of the study was to evaluate the temporal patterns of dengue incidence from 2001 to 2014 and forecast for 2015 in two Brazilian cities. We analysed dengue surveillance data (SINAN) from Recife, 1.6 million population, and Goiania, 1.4 million population. We used Auto-Regressive Integrated Moving Average (ARIMA) modelling of monthly notified dengue incidence (2001-2014). Forecasting models (95% prediction interval) were developed to predict numbers of dengue cases for 2015. During the study period, 73,479 dengue cases were reported in Recife varying from 11 cases/100,000 inhab (2004) to 2418 cases/100,000 inhab (2002). In Goiania, 253,008 dengue cases were reported and the yearly incidence varied from 293 cases/100,000 inhab (2004) to 3927 cases/100,000 inhab (2013). Trend was the most important component for Recife, while seasonality was the most important one in Goiania. For Recife, the best fitted model was ARIMA (1,1,3)12 and for Goiania Seasonal ARIMA (1,0,2) (1,1,2)12. The model predicted 4254 dengue cases for Recife in 2015; SINAN registered 35,724 cases. For Goiania the model predicted 33,757 cases for 2015; the reported number of cases by SINAN was 74,095, within the 95% prediction interval. The difference between notified and forecasted dengue cases in Recife can be explained by the co-circulation of dengue and Zika virus in 2015. In this year, all cases with rash were notified as "dengue-like" illness. The ARIMA models may be considered a baseline for the time series analysis of dengue incidence before the Zika epidemic.

Parity of indigenous and non-indigenous women in Brazil: does the reported number of children born depend upon who answers national census questions?

Taking parity as the main analytic variable, the objective of this study is to investigate whether the patterns of response to national census questions in Brazil differ when Indigenous and non-Indigenous women are compared, taking into consideration whether the information was provided by the women directly or by a proxy respondent (another household member or a non-resident). We use data on children ever born to Indigenous and non-Indigenous women from two Brazilian regions, the Northeast and the North. Data on the number of household members, total household rooms, interviewee's color/race, educational attainment, age, parity, and type of respondent were obtained from the 2010 Brazilian census. The relation between color/race and reported parity, as well as the impact of the type of respondent on this association were assessed with the Zero-inflated Negative Binomial regression, stratified by region (North and Northeast) and urban/rural status. Just over half of census interviewees answered directly the census questions (51.2% in the North and 54.4% in the Northeast). Indigenous women in the North region had the highest percentage of interviews carried out with a non-resident (12.7% total; 15.0% and 3.0% in rural and urban areas, respectively). Regardless of color/race, parity means were considerably higher when the question was answered by the woman directly (93.5%-101.4% and 15.6%-21.7% higher, compared co-resident and non-resident based answers, respectively). Parity underreporting was particularly strong in Indigenous women living in the rural North (16.0% less in comparison to White women). Proxy respondents tend to underestimate the count of children, particularly among Indigenous women from the North. The implementation of certain methodological alternatives in the Brazilian national censuses, such as the selection and training of census takers to work specifically in Indigenous territories, might be a productive means to improve data collection.

Single nucleotide polymorphisms in candidate genes and dengue severity in children: a case-control, functional and meta-analysis study.

Dengue is an arthropod-borne emerging viral disease with high morbidity and mortality risk in tropical countries like Brazil. Clinical manifestations are vast, ranging from asymptomatic to most severe forms of dengue such as shock. Previous data have shown that host genetics play a role in disease susceptibility and severity. Herein, we have tested the association of single nucleotide polymorphisms (SNPs) at TNF, IL10, MIF, DCSIGN, CLEC5A, NOD2, CCR5 and MRC1 as candidate genes using a matched case-control study design including 88 severe children cases of dengue patients and 335 healthy unrelated subjects that was also separated in IgG(+) and IgG(-) controls. We demonstrated that the TT genotype of CLEC5A SNP (rs1285933 C>T) is associated with dengue severity (OR=2.25; p=0.03) and that GG genotype of -336G>A DCSIGN (CD209) SNP is associated with protection to severe dengue (OR=0.12; p=0.04). Both comparisons were borderline significant when cases were compared with IgG(+) controls subgroup. Nevertheless, genotype-phenotype correlation was also assessed using serum levels of TNF from infected patients at the onset of dengue fever, and CT/TT carriers in CLEC5A secreted higher levels of TNF than CC individuals in 5-7 days of infection. No significant difference was observed in TNF levels between genotypes GG versus AG/AA at DCSIGN promoter. Next, we performed a meta-analysis retrieving results from the literature for -336G>A DCSIGN and -308G>A TNF SNPs demonstrating that the consensus estimates of these SNPs indicated no association with dengue severity (when compared to Dengue fever) in the overall analysis. But, a subgroup analysis in the -336G>A DCSIGN, the G allele was associated with severe dengue susceptibility in Asians (ORallele=2.77; p=0.0001; ORcarriers=2.99; p=0.0001) and protection in Brazilians (ORallele=0.66; p=0.013). In summary, our results suggest that genetic variations at CLEC5A increase the risk and regulate TNF secretion in dengue severity among Brazilians. Also, combined data of the literature suggest population-specific effect of the -336 DCSIGN SNP more prominent in Asians and in a different direction than Brazilians.