PIN107 - BACTERIAL SKIN AND SOFT TISSUE INFECTIONS: GLOBAL MAPPING BY GEOGRAPHICAL DISTRIBUTION AND CLIMATE AREA

Abstract

The aim of this study was to describe the geographical distribution of bacterial skin and soft tissue infections (SSTIs) worldwide, as well as the depicted climate areas (tropical, dry, temperate, continental and polar). A systematic literature search was conducted through the PubMed database to identify the available evidence on bacterial SSTIs related to climate and humidity conditions. Two search strategies were designed taking into consideration terms located by MeSH vocabulary. Two additional filters were applied to search results (1. abstract availability; 2. title + abstract screening, in order to identify reports of bacterial SSTIs). No time or language limit was determined. The identified studies were evaluated by two independent reviewers to assess their inclusion in this project. The spatial analysis was developed with the GeoDa 1.8 software. All search strategies resulted in 1,284 results. Duplicates removal and inclusion criteria application resulted in 675 references for analysis, 106 of which reported bacterial SSTIs. Global results showed that the climate areas with most casuistry were temperate and tropical (79% and 49% of studies respectively). More than 45% of the studies analyzed reported infections related to Staphylococcus and Streptococcus (abscess, cellulitis, furunculosis, impetigo and pyoderma). Even though variability in geographical distribution was too high, more tan 50% of reported evidence was specific for Europe, the United States and Canada. World maps of Köppen-Geiger climate classification with specific results for bacterial SSTIs will be disclosed. Climate mapping for SSTIs is a key epidemiological tool for Dermatology and Public Health. However, the evidence of bacterial SSTIs is scarce and this makes it difficult to identify high-risk populations. This situation is specially relevant in resource-limited settings, where the burden of these diseases is more relevant in endemic populations.