Identifying the spatial patterning characteristics of HIV positive clients not linked to care using a geographic information system
| Autor: | Kevin Rombosia, Douglas Olaka, Evans Ondura, Nelly Rangara, Bernard Mitto, Elizabeth Oele, Nancy Kirui |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Geographic information system
General Immunology and Microbiology business.industry 05 social sciences 0211 other engineering and technologies Human immunodeficiency virus (HIV) 02 engineering and technology General Medicine Standard score medicine.disease_cause 050105 experimental psychology General Biochemistry Genetics and Molecular Biology Geocoding medicine Information system 0501 psychology and cognitive sciences Residence General Pharmacology Toxicology and Pharmaceutics Psychology business Spatial analysis psychological phenomena and processes Statistic 021101 geological & geomatics engineering Demography |
| Zdroj: | F1000Research. 9:515 |
| ISSN: | 2046-1402 |
| DOI: | 10.12688/f1000research.23967.1 |
| Popis: | Background: Linkage to care is a crucial early step in successful HIV treatment. This study sought to identify the spatial patterning characteristics of HIV positive clients that are not linked to care in the Kisumu West HIV program using a geographic information system. Methods: The geocodes of HIV positive, non-linked clients’ residences were exported to ArcGIS software. The spatial patterning characteristics of HIV clients that are testing positive and not linked to care was described using Global Moran’s I statistic, which is a measure of spatial autocorrelation. Results: A total of 14,077 clients were tested for HIV. Of clients testing positive for HIV, 10% (n=34) were not yet linked to care two weeks after the diagnosis of HIV. Of the HIV positive non-linked clients, most (65%; n= 32) had spatially identifiable data about where they resided. Regarding the spatial patterning characteristics of the clients who tested HIV positive but were not linked to care and with spatially identifiable residence information, the Global Moran I statistic for autocorrelation was 0.435 (z score 1.383, p- value 0.167). Conclusion: By using age as an attribute value, the spatial distribution of clients testing HIV positive and not being linked to care is random. Geographical information systems can be used to identify the spatial patterning characteristics of HIV positive clients that are not linked to care. A key requirement to achieving this would require the collection of precise and accurate spatially identifiable locator information but without compromising patient confidentiality. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|