Estimating hidden populations by transferring knowledge from geographically misaligned levels.

The estimation of hidden sub-populations is a hard task that appears in many fields. For example, public health planning in Brazil depends crucially of the number of people who holds a private health insurance plan and hence rarely uses the public services. Different sources of information about these sub-populations may be available at different geographical levels.

Where did I get dengue? Detecting spatial clusters of infection risk with social network data.

Typical spatial disease surveillance systems associate a single address to each disease case reported, usually the residence address. Social network data offers a unique opportunity to obtain information on the spatial movements of individuals as well as their disease status as cases or controls. This provides information to identify visit locations with high risk of infection, even in regions where no one lives such as parks and entertainment zones.

A random-censoring Poisson model for underreported data.

A major challenge when monitoring risks in socially deprived areas of under developed countries is that economic, epidemiological, and social data are typically underreported. Thus, statistical models that do not take the data quality into account will produce biased estimates. To deal with this problem, counts in suspected regions are usually approached as censored information.

Schistosoma mansoni reinfection: Analysis of risk factors by classification and regression tree (CART) modeling.

Praziquantel (PZQ) is an effective chemotherapy for schistosomiasis mansoni and a mainstay for its control and potential elimination. However, it does not prevent against reinfection, which can occur rapidly in areas with active transmission. A guide to ranking the risk factors for Schistosoma mansoni reinfection would greatly contribute to prioritizing resources and focusing prevention and control measures to prevent rapid reinfection.

Sensing in the collaborative Internet of Things.

We are entering a new era of computing technology, the era of Internet of Things (IoT). An important element for this popularization is the large use of off-the-shelf sensors. Most of those sensors will be deployed by different owners, generally common users, creating what we call the Collaborative IoT.

A critical look at prospective surveillance using a scan statistic.

The scan statistic is a very popular surveillance technique for purely spatial, purely temporal, and spatial-temporal disease data. It was extended to the prospective surveillance case, and it has been applied quite extensively in this situation. When the usual signal rules, as those implemented in SaTScan(TM) (Boston, MA, USA) software, are used, we show that the scan statistic method is not appropriate for the prospective case.

Relative risk estimates from spatial and space-time scan statistics: are they biased?

The purely spatial and space-time scan statistics have been successfully used by many scientists to detect and evaluate geographical disease clusters. Although the scan statistic has high power in correctly identifying a cluster, no study has considered the estimates of the cluster relative risk in the detected cluster. In this paper, we evaluate whether there is any bias on these estimated relative risks.

Relative risk of visceral leishmaniasis in Brazil: a spatial analysis in urban area.

Background: Visceral leishmaniasis (VL) is a vector-borne disease whose factors involved in transmission are poorly understood, especially in more urban and densely populated counties. In Brazil, the VL urbanization is a challenge for the control program. The goals were to identify the greater risk areas for human VL and the risk factors involved in transmission.

Bayes plus Brass: estimating total fertility for many small areas from sparse census data.

Estimates of fertility in small areas are valuable for analysing demographic change, and important for local planning and population projection. In countries lacking complete vital registration, however, small-area estimates are possible only from sparse survey or census data that are potentially unreliable. In these circumstances estimation requires new methods for old problems: procedures must be automated if thousands of estimates are required; they must deal with extreme sampling variability in many areas; and they should also incorporate corrections for possible data errors.

Mapping the Timing, Pace, and Scale of the Fertility Transition in Brazil.

Between 1960 and 2000, fertility fell sharply in Brazil, but this transition was unevenly distributed in space and time. Using Bayesian spatial statistical methods and microdata from five censuses, we develop and apply a procedure for fitting logistic curves to the fertility transitions in more than 500 small regions of Brazil over this 40-year period. Doing so enables us to map the main features of the Brazilian fertility transition in considerable detail.

Impact of the Staying Alive Program on the reduction of homicides in a community in Belo Horizonte.

Objective: To evaluate the impact of a homicide prevention program.

Methods: A quasi-experimental study was performed using time series analysis of homicide incidence in the Morro das Pedras area in the city of Belo Horizonte, Southeastern Brazil, from 2002 to 2006. The number of homicides occurring in this location was compared to other violent and non-violent favelas and to other neighborhoods of the city, during each of the Program phases.

[Intra-urban dynamics of dengue epidemics in Belo Horizonte, Minas Gerais State, Brazil, 1996-2002].

This study aimed to describe the temporal-spatial patterns of dengue epidemics in Belo Horizonte, Minas Gerais State, Brazil, from 1996 to 2002 and to analyze residential address as a proxy for exposure. Reported dengue cases were analyzed according to week of onset of symptoms and residential census tract. Local Moran's index was used to assess spatial autocorrelation of incidence coefficients, and recurrent census areas over different epidemic waves were also verified.

Spatial vulnerability to dengue in a Brazilian urban area during a 7-year surveillance.

This study considers the vulnerability of the urban area of the City of Belo Horizonte to dengue. A total number of 89,607 cases registered in the surveillance system from 1996 to 2002 were analyzed. Seven epidemic waves were identified during this period.

Empirical Bayes estimation of demographic schedules for small areas.

In this article, we analyze empirical Bayes (EB) methods for estimating small-area rate schedules. We develop EB methods that treat schedules as vectors and use adaptive neighborhoods to keep estimates appropriately local. This method estimates demographic rates for local subpopulations by borrowing strength not only from similar individuals elsewhere but also from other groups in the same area and from regularities in schedules across locations.

[Regionalization as a strategy for the definition of homicide-control public policies].

This article analyzes the spatial distribution of homicide rates in Minas Gerais State, Brazil, using data from the Ministry of Health Mortality Information System (SIM/MS) from 1996 to 2000. Population data used to calculate rates were also obtained from the Brazilian Ministry of Health. Minas Gerais has a large territory, so the study used a recently developed statistical methodology implemented in the SKATER software to generate homogeneous spatial clusters.

Multiple cancer sites incidence rates estimation using a multivariate Bayesian model.

Background: In Brazil cancer incidence rates have to be estimated from occasional surveys, due to lack of continuous cancer registries. Many estimated rates have very large variances, because only few years of data were collected. When dealing with a single cancer site, it is possible to adopt a Bayesian method which borrows information about the cancer rates from other geographical areas to estimate the cancer rate in a given area.

[Data comparison on homicide deaths between two information systems, Brazil].

Introduction: There is much criticism on the quality of criminal data available in Brazil, but there lacks systematic studies to corroborate it. Thus, it was conducted a comparison between homicides registered in Minas Gerais by two public information systems.

Methods: The number of homicide deaths of the Mortality Information System of the Ministry of Health (SIM/MS) and Minas Gerais Military Police (PMMG), from 1979 to 1998, were assessed.

A Bayesian space varying parameter model applied to estimating fertility schedules.

We propose a spatial generalized linear model (GLM) to analyse the vital rates for small areas. In each small area, we have a response vector and covariates to explain its variability. The statistical methodology is based on a spatial Bayesian approach and it allows the covariates' parameters of the generalized linear model to vary smoothly on space.