Spatial approach of leprosy in the State of São Paulo, 2009-2012

Decline in Vaccination Coverage against Poliomyelitis in the municipalities of Vale do Paraíba (SP) under a spatial approach

OBJECTIVE

To analyze vaccination coverage (VC) for polio in the municipalities of Vale do Paraíba in the State of São Paulo.

METHODS

This is an ecological and exploratory study of VC in 35 municipalities using a spatial approach; VC data were obtained from the IT Department of the Unified Health System (DATASUS), for the years 2015 and 2019, and categorized into Low (VC<95%) and ideal (≥95%). Information was obtained on gross domestic product (GDP), professional rates and number of basic health units (UBS) and maternal data such as age, marital status (MS) and education. Univariate and bivariate Moran indices were estimated for the years 2015 and 2019, and thematic maps were created for CV values.

RESULTS

The average VC values were 107.7%±27.2 in 2015, and 94.2%±27.8 in 2019 (p<0.05). In 2015 vs. 2019, there were 10 vs. 25 municipalities in the Low category. In 2015, the variables VC, number of UBS, age, education, and MS were spatially correlated, but in 2019 only maternal age and education were spatially correlated. The bivariate Moran was significant and negative for VC in 2019 with maternal education. There was an increase in municipalities with worsening VC values.

CONCLUSIONS

The spatial approach identified a decrease in polio vaccination coverage in the studied region.

Geospatial epidemiology of leprosy in northwest Bangladesh: a 20-year retrospective observational study

Background

Leprosy is known to be unevenly distributed between and within countries. High risk areas or ‘hotspots’ are potential targets for preventive interventions, but the underlying epidemiologic mechanisms that enable hotspots to emerge, are not yet fully understood. In this study, we identified and characterized leprosy hotspots in Bangladesh, a country with one of the highest leprosy endemicity levels globally.

Methods

We used data from four high-endemic districts in northwest Bangladesh including 20 623 registered cases between January 2000 and April 2019 (among ~ 7 million population). Incidences per union (smallest administrative unit) were calculated using geospatial population density estimates. A geospatial Poisson model was used to detect incidence hotspots over three (overlapping) 10-year timeframes: 2000–2009, 2005–2014 and 2010–2019. Ordinal regression models were used to assess whether patient characteristics were significantly different for cases outside hotspots, as compared to cases within weak (i.e., relative risk (RR) of one to two), medium (i.e., RR of two to three), and strong (i.e., RR higher than three) hotspots.

Results

New case detection rates dropped from 44/100 000 in 2000 to 10/100 000 in 2019. Statistically significant hotspots were identified during all timeframes and were often located at areas with high population densities. The RR for leprosy was up to 12 times higher for inhabitants of hotspots than for people living outside hotspots. Within strong hotspots (1930 cases among less than 1% of the population), significantly more child cases (i.e., below 15 years of age) were detected, indicating recent transmission. Cases in hotspots were not significantly more likely to be detected actively.

Conclusions

Leprosy showed a heterogeneous distribution with clear hotspots in northwest Bangladesh throughout a 20-year period of decreasing incidence. Findings confirm that leprosy hotspots represent areas of higher transmission activity and are not solely the result of active case finding strategies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40249-021-00817-4.

Integrated environmental vulnerability to oil spills in sensitive areas

As the typical range of influence of oil spills surrounds urbanised and economically active areas, it is likely that fragile regions may not be part of the most vulnerable zones. This premise is remediated in this paper with the adoption of a vulnerability approach based on the integration of static and dynamic information, such as oil pollution susceptibility. Susceptibility is a poorly consolidated term and is often used as synonym for environmental sensitivity; it is considered here to be the distribution areas of oil slicks. To test the proposed approach, an integrated estimation of environmental vulnerability is carried out for an environmentally sensitive area in the south of Brazil by merging static data inherent to the medium with information of a dynamic nature related to trajectory, behaviour and the fate of oil at sea. Moreover, the oil pollution intensity and environmental sensitivity data in susceptible areas are addressed. Subsequently, the environmental vulnerability is estimated by integrating hazard maps, concentrations and losses of the mass of the oil slick, oil beaching time and the littoral sensitivity index hierarchy. Results will prove to be useful to highlight critical areas for which the highest levels of severity are expected, which can lead to improvements in decision-making processes to support oil-spill prevention, as well as improve response readiness, especially in developing countries that have historically under-protected their sensitive regions.