ABSTRACT
Building fair, equitable, and beneficial partnerships between institutions collaborating in research in low- and middle-income countries (LMIC) and high-income countries (HIC) has become an integral part of research capacity building in global health in recent years. In this paper, we offer an example of an academic collaboration between the University of California Los Angeles, Center for Health Policy and Research (UCLA CHPR) and the University of Philippines, Manila, College of Public Health (UPM CPH) that sought to build an equitable partnership between research institutions. The partnership was built on a project to build capacity for research and produce data for policy action for the prevention and care of non-communicable diseases (NCDs) through primary healthcare in the Philippines. The specific objectives of the project were to: (1) locally adapt the Primary Care Assessment Tool for the Philippines and use the adapted tool to measure facility-level primary care delivery, (2) conduct focus group discussions (FGDs) to gather qualitative observations regarding primary care readiness and capacity, and (3) conduct a comprehensive population-based health survey among adults on NCDs and prior healthcare experience. We describe here the progression of the partnership between these institutions to carry out the project and the elements that helped build a stronger connection between the institutions, such as mutual goal setting, cultural bridging, collaborative teams, and capacity building. This example, which can be used as a model depicting new directionality and opportunities for LMIC-HIC academic partnerships, was written based on the review of shared project documents, including study protocols, and written and oral communications with the project team members, including the primary investigators. The innovation of this partnership includes: LMIC-initiated project need identification, LMIC-based funding allocation, a capacity-building role of the HIC institution, and the expansion of scope through jointly offered courses on global health.
Subject(s)
Capacity Building , Global Health , Adult , Humans , Capacity Building/methods , Philippines , Delivery of Health Care , Primary Health CareABSTRACT
BACKGROUND: Dengue remains a major public health problem in the Philippines, particularly in urban areas of the National Capital Region. Thematic mapping using geographic information systems complemented by spatial analysis such as cluster analysis and hot spot detection can provide useful information to guide preventive measures and control strategies against dengue. Hence, this study was aimed to describe the spatiotemporal distribution of dengue incidence and identify dengue hot spots by barangay using reported cases from Quezon City, the Philippines from 2010 to 2017. METHODS: Reported dengue case data at barangay level from January 1, 2010 to December 31, 2017 were obtained from the Quezon City Epidemiology and Surveillance Unit. The annual incidence rate of dengue from 2010 to 2017, expressed as the total number of dengue cases per 10,000 population in each year, was calculated for each barangay. Thematic mapping, global cluster analysis, and hot spot analysis were performed using ArcGIS 10.3.1. RESULTS: The number of reported dengue cases and their spatial distribution varied highly between years. Local clusters were evident during the study period. Eighteen barangays were identified as hot spots. CONCLUSIONS: Considering the spatial heterogeneity and instability of hot spots in Quezon City across years, efforts towards the containment of dengue can be made more targeted, and efficient with the application of hot spot analysis in routine surveillance. This may be useful not only for the control of dengue but also for other diseases, and for public health planning, monitoring, and evaluation.
ABSTRACT
OBJECTIVES: This paper was undertaken to explore the relationship of a 4-year period dengue incidence and the interplay of selected spatial factors (i.e., build-up structures, existing land use/cover types, and presence of water networks) in Quezon City, Philippines. It attempts to examine why dengue incidences are higher in some areas, looking at factors such as geographical attributes, livelihood activities, and practices in the area. At the end of this paper, dengue risk maps will be produced to guide local health authorities target specific areas for focused interventions to manage future dengue outbreak in the area. METHODS: Reports on dengue cases over the 4-year period (2005-2008) from the City's Health Department Office were encoded and exported in ArcGIS 9.1, a Geographic Information Systems (GIS) mapping software technology. Together with the city's environmental conditions, dengue frequencies were mapped out, overlaid, and examined to determine whether or not these environmental factors affect, contribute and link to the dengue occurrence in an area. RESULTS: After rendering the dengue risk maps, the highest frequency of dengue is evident in the eastern portion of Quezon City covering District II. Overlaying or superimposing dengue frequency layers with the spatial factors being considered in this study has revealed that these factors affect and contribute to the occurrence of dengue in an area. Areas with a number of river networks and built-up structures experience high dengue incidence. Lands used for residential purposes with neighboring commercial/industrial structures also tend to be dengue susceptible. However, the population density factor alone does not necessarily translate to high dengue frequency. Barangays (the smallest administrative divisions of the city) with high recorded dengue frequency are areas within or near dumpsite facilities primarily because of sanitation concerns as well as the type of livelihood and inherent practices of majority of the residents. CONCLUSIONS: This research provides an understanding of the spatial epidemiology of dengue in Quezon City using GIS as a tool for identifying high risk areas for dengue. Spatial examination has been carried out to determine spatial anomalies (high concentration of incidence) and the spatial makeup of the area that affects or contributes to such anomalies. The role of GIS in public health decision-making is evident in identifying high risk areas and creating dengue risk maps. Local health authorities will be in a better position to target priority areas and decide where to put scarce resources for programs and projects that will address further disease outbreaks.
