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1.
Sci Rep ; 10(1): 13767, 2020 08 13.
Article in English | MEDLINE | ID: mdl-32792543

ABSTRACT

To examine the effects of poor sanitation and hygiene on the prevalence of antimicrobial-resistant bacteria, we surveyed households in two rural and two urban communities in Guatemala (N = 196 randomly selected households). One adult (≥ 18-years old) and, when available, one child (≤ 5 years-old) provided a stool sample. Up to 48 presumptive Escherichia coli isolates were collected from each stool sample (n = 21,256 total) and were subjected to breakpoint assays for ten antibiotics. Mixed-effects logistic models were used to identify potential factors influencing the likelihood of harboring antibiotic-resistant bacteria. For nine out of ten antibiotics, the odds of detecting resistant bacteria decreased by ~ 32% (odds ratios, OR 0.53-0.8, P < 0.001) for every unit of improvement of a hygiene scale. Hygiene differences between households had a greater impact on prevalence compared to antibiotic use differences. The likelihood of detecting resistant isolates was lower for five antibiotics among households that boiled raw milk before consumption (OR 0.31-0.69), and higher for nine antibiotics in urban households (OR > 1.89-9.6). Poor hygiene conditions likely obscure effects of individual antibiotic use, presumably due to enhanced microbial transmission. Consequently, efforts to improve antibiotic stewardship should be coupled with improving hygiene conditions.


Subject(s)
Drug Resistance, Multiple, Bacterial/physiology , Escherichia coli Infections/epidemiology , Hygiene , Poverty , Sanitation/methods , Adult , Anti-Bacterial Agents/pharmacology , Child, Preschool , Escherichia coli/drug effects , Escherichia coli/isolation & purification , Escherichia coli Infections/transmission , Guatemala/epidemiology , Humans , Microbial Sensitivity Tests , Public Health/methods , Residence Characteristics , Surveys and Questionnaires
2.
PLoS One ; 10(11): e0141113, 2015.
Article in English | MEDLINE | ID: mdl-26528911

ABSTRACT

Injury is a leading cause of the global disease burden, accounting for 10 percent of all deaths worldwide. Despite 90 percent of these deaths occurring in low and middle-income countries (LMICs), the majority of trauma research and infrastructure development has taken place in high-income settings. Furthermore, although accessible services are of central importance to a mature trauma system, there remains a paucity of literature describing the spatial accessibility of emergency services in LMICs. Using data from the Service Provision Assessment component of the Demographic and Health Surveys of Namibia and Haiti we defined the capabilities of healthcare facilities in each country in terms of their preparedness to provide emergency services. A Geographic Information System-based network analysis method was used to define 5- 10- and 50-kilometer catchment areas for all facilities capable of providing 24-hour care, higher-level resuscitative services or tertiary care. The proportion of a country's population with access to each level of service was obtained by amalgamating the catchment areas with a population layer. A significant proportion of the population of both countries had poor spatial access to lower level services with 25% of the population of Haiti and 51% of the population of Namibia living further than 50 kilometers from a facility capable of providing 24-hour care. Spatial access to tertiary care was considerably lower with 51% of Haitians and 72% of Namibians having no access to these higher-level services within 50 kilometers. These results demonstrate a significant disparity in potential spatial access to emergency services in two LMICs compared to analogous estimates from high-income settings, and suggest that strengthening the capabilities of existing facilities may improve the equity of emergency services in these countries. Routine collection of georeferenced patient and facility data in LMICs will be important to understanding how spatial access to services influences outcomes.


Subject(s)
Developing Countries , Emergency Medical Services , Geographic Information Systems , Health Services Accessibility , Tertiary Care Centers , Wounds and Injuries/therapy , Haiti , Humans , Namibia , Socioeconomic Factors
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