Spatial analysis of gestational anemia in Peru, 2015 [Análisis espacial de la anemia gestacional en el Perú, 2015]

Objectives. To establish regional prevalences of anemia in pregnant women receiving care at public clinics in Peru in 2015 and identify high-prevalence district conglomerates. Materials and Methods. An ecological study was carried out on data from pregnant women with anemia registered on the Nutritional Status Information System (SIEN) who received care in 7703 public clinics in 2015. Regional and district prevalences of gestational anemia were calculated. District conglomerates with a high prevalence of gestational anemia were identified using the Moran Index. Results. Information was gathered from 311,521 pregnant women distributed in 1638 districts in Peru. The national prevalence of anemia was 24.2% (95% confidence interval [95% CI]: 24.0-24.3%), the rural prevalence was 30.5%, and the urban prevalence was 22.0%. The regions of Huancavelica (45.5%; 95% CI: 44.2-46.7%), Puno (42.8%; 95% CI: 41.9-43.7%), Pasco (38.5%; 95% CI: 36.9-40.0%), Cusco (36.0%; 95% CI: 35.3-36.8%), and Apurímac (32.0%; 95% CI: 30.8-33.1%) had the highest prevalences of anemia. The local Moran Index identified 202 high-priority districts (hot spots) (12.3% of total; 44 urban and 158 rural) located in Ancash, Apurímac, Arequipa, Ayacucho, Cajamarca, Cusco, Huancavelica, Huánuco, Junín, La Libertad, Lima, Pasco, and Puno containing high-prevalence district conglomerates. Conclusions. Gestational anemia in Peru has its highest prevalence rates in rural and southern mountainous areas. The district conglomerates with high prevalence rates of gestational anemia coincide with the areas of high regional prevalence. © 2017, Instituto Nacional de Salud. All rights reserved

Spatial analysis of childhood obesity and overweight in Peru, 2014 [Análisis espacial del sobrepeso y la obesidad infantil en el Perú, 2014]

Objectives. To estimate regional prevalence and identify the spatial patterns of the degree of overweight and obesity by districts in under five years children in Peru during 2014. Materials and methods. Analysis of the information reported by the Information System Nutritional Status (SIEN) of the number of cases of overweight and obesity in children under five years recorded during 2014. Regional prevalence for overweight and obesity, and their respective confidence intervals to 95% were calculated. Moran index was used to determine patterns of grouping districts with high prevalence of overweight and/or obesity. Results. Data from 1834 districts and 2,318,980 children under five years were analyzed. 158,738 cases (6.84%; CI 95%: 6.81 to 6.87) were overweight, while 56,125 (2.42%; CI 95%: 2.40 to 2.44) obesity. The highest prevalence of overweight were identified in the regions of Tacna (13.9%), Moquegua (11.8%), Callao (10.4%), Lima (10.2%) and Ica (9.3%), and in the same regions for obesity with 5.3%; 4.3%; 4.0%; 4.0% and 3.8% respectively. The spatial analysis found grouping districts of high prevalence in 10% of all districts for both overweight and obesity, identifying 199 districts for overweight (126 urban and 73 rural), and 184 for obesity (136 urban and 48 rural). Conclusions. The highest prevalence of overweight and obesity were identified in the Peruvian coast regions. Moreover, these regions are predominantly exhibited a spatial clustering of districts with high prevalence of overweight and obesity. © 2016, Instituto Nacional de Salud. All rights reserved

HIT-COVID, a global database tracking public health interventions to COVID-19

The COVID-19 pandemic has sparked unprecedented public health and social measures (PHSM) by national and local governments, including border restrictions, school closures, mandatory facemask use and stay at home orders. Quantifying the effectiveness of these interventions in reducing disease transmission is key to rational policy making in response to the current and future pandemics. In order to estimate the effectiveness of these interventions, detailed descriptions of their timelines, scale and scope are needed. The Health Intervention Tracking for COVID-19 (HIT-COVID) is a curated and standardized global database that catalogues the implementation and relaxation of COVID-19 related PHSM. With a team of over 200 volunteer contributors, we assembled policy timelines for a range of key PHSM aimed at reducing COVID-19 risk for the national and first administrative levels (e.g. provinces and states) globally, including details such as the degree of implementation and targeted populations. We continue to maintain and adapt this database to the changing COVID-19 landscape so it can serve as a resource for researchers and policymakers alike