Spatial analysis of factors associated with HIV infection among young people in Uganda, 2011

Chimoyi, Lucy; Musenge, Eustasius

doi:10.1186/1471-2458-14-555

Cited by 51 publications

(61 citation statements)

References 44 publications

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“…Nevertheless, the combination of interpolation and cluster detection methods provides some confidence that the results reliably describe geographic variation in HIV prevalence within a generalized epidemic, as was shown in studies with similar methods [1,5]. Moreover, self-reported variables, particularly relating to sexual behaviour, may be subject to recall and social desirability bias [31], although a secret voting method was used to minimize social desirability bias for sexual behaviour variables [34].…”

Section: Discussionmentioning

confidence: 99%

“…Geographic variation in HIV prevalence and incidence has been demonstrated even in generalized epidemics in eastern and southern sub-Saharan Africa [1][2][3][4][5][6][7]. Currently, there is great interest amongst public health planners in whether this geographic variation could be used to increase the cost-effectiveness of HIV/AIDS interventions by focusing interventions towards areas of highest need [6,[8][9][10].…”

Section: Introductionmentioning

confidence: 99%

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Spatial patterns of HIV prevalence and service use in East Zimbabwe: implications for future targeting of interventions

Schaefer

Gregson

Takaruza

et al. 2017

Journal of the International AIDS Society

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Introduction: Focusing resources for HIV control on geographic areas of greatest need in countries with generalized epidemics has been recommended to increase cost-effectiveness. However, socioeconomic inequalities between areas of high and low prevalence could raise equity concerns and have been largely overlooked. We describe spatial patterns in HIV prevalence in east Zimbabwe and test for inequalities in accessibility and uptake of HIV services prior to the introduction of spatially-targeted programmes. Methods: 8092 participants in an open-cohort study were geo-located to 110 locations. HIV prevalence and HIV testing and counselling (HTC) uptake were mapped with ordinary kriging. Clusters of high or low HIV prevalence were detected with Kulldorff statistics, and the socioeconomic characteristics and sexual risk behaviours of their populations, and levels of local HIV service availability (measured in travel distance) and uptake were compared. Kulldorff statistics were also determined for HTC, antiretroviral therapy (ART), and voluntary medical male circumcision (VMMC) uptake. Results: One large and one small high HIV prevalence cluster (relative risk [RR] = 1.78, 95% confidence interval [CI] = 1.53–2.07; RR = 2.50, 95% CI = 2.08–3.01) and one low-prevalence cluster (RR = 0.70, 95% CI = 0.60–0.82) were detected. The larger high-prevalence cluster was urban with a wealthier population and more high-risk sexual behaviour than outside the cluster. Despite better access to HIV services, there was lower HTC uptake in the high-prevalence cluster (odds ratio [OR] of HTC in past three years: OR = 0.80, 95% CI = 0.66–0.97). The low-prevalence cluster was predominantly rural with a poorer population and longer travel distances to HIV services; however, uptake of HIV services was not reduced. Conclusions: High-prevalence clusters can be identified to which HIV control resources could be targeted. To date, poorer access to HIV services in the poorer low-prevalence areas has not resulted in lower service uptake, whilst there is significantly lower uptake of HTC in the high-prevalence cluster where health service access is better. Given the high levels of risky sexual behaviour and lower uptake of HTC services, targeting high-prevalence clusters may be cost-effective in this setting. If spatial targeting is introduced, inequalities in HIV service uptake may be avoided through mobile service provision for lower prevalence areas.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatial patterns of HIV prevalence and service use in East Zimbabwe: implications for future targeting of interventions

Schaefer

Gregson

Takaruza

et al. 2017

Journal of the International AIDS Society

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“…The use of spatial-temporal cluster analysis has been applied for the detection of infectious disease hotspots in recent years [3–5]. It has also been successfully used for the identification of TB clusters, with meaningful results yielded [6–8].…”

Section: Introductionmentioning

confidence: 99%

Spatial-temporal analysis of pulmonary tuberculosis in the northeast of the Yunnan province, People’s Republic of China

Huang

Abe

et al. 2017

Infect Dis Poverty

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BackgroundThe number of pulmonary tuberculosis (PTB) cases in China ranks third in the world. A continuous increase in cases has recently been recorded in Zhaotong prefecture-level city, which is located in the northeastern part of Yunnan province. This study explored the space-time dynamics of PTB cases in Zhaotong to provide useful information that will help guide policymakers to formulate effective regional prevention and control strategies.MethodsThe data on PTB cases were extracted from the nationwide tuberculosis online registration system. Time series and spatial cluster analyses were applied to detect PTB temporal trends and spatial patterns at the town level between 2011 and 2015 in Zhaotong. Three indicators of PTB treatment registration history were used: initial treatment registration rate, re-treatment registration rate, and total PTB registration rate.ResultsSeasonal trends were detected with an apparent symptom onset peak during the winter season and a registration peak during the spring season. A most likely cluster and six secondary clusters were identified for the total PTB registration rate, one most likely cluster and five secondary clusters for the initial treatment registration rate, and one most likely cluster for the re-treatment registration rate. The most likely cluster of the three indicators had a similar spatial distribution and size in Zhenxiong County, which is characterised by a poor socio-economic level and the largest population in Yunnan.ConclusionThis study identified temporal and spatial distribution of PTB in a high PTB burden area using existing health data. The results of the study provide useful information on the prevailing epidemiological situation of PTB in Zhaotong and could be used to develop strategies for more effective PTB control at the town level. The cluster that overlapped the three PTB indicators falls within the geographic areas where PTB control efforts should be prioritised.

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“…The Afar rate is nearly double the national average, while Somalis had a relatively low prevalence (CSA & ICF International, 2012). In Uganda, some of the highest HIV prevalence rates were reported from the pastoral nomadic areas in the northern parts of the country (Chimoyi & Musenge, 2011). A study in South Omo Zone in south-western Ethiopia predicted the spread of HIV after the opening of an all-weather road from Addis Ababa, which facilitates the movement of farmers, tourists and traders from the highlands to the land of the Hamer pastoralists.…”

Section: Hiv Prevalence and Risk Of Exposure Among Pastoral Communitiesmentioning

confidence: 99%

HIV/AIDS among pastoralists and refugees in north-east Africa: a neglected problem

Kaba

Mariam

Kassa³

et al. 2016

African Journal of AIDS Research

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The eight member states (Djibouti, Eritrea, Ethiopia, Kenya, Somalia, South Sudan, Sudan and Uganda) of the Intergovernmental Authority for Development (IGAD) have the largest proportions of cross-border mobile pastoralists and refugees in Africa. Although all IGAD countries have had national HIV/AIDS prevention, care and treatment programmes since the late 1980s, the IGAD Regional HIV & AIDS Partnership Program was (IRAPP) established in 2007 to mitigate the challenges of HIV among neglected pastoral and refugee communities. This article assesses vulnerability of pastoralists and refugee communities to HIV and interventions targeting these groups in the IGAD countries. Outcomes from this study may serve as a baseline for further research and to improve interventions. Published articles were accessed through web searches using PubMed and Google Scholar engines and unpublished documents were collected manually. The search terms were HIV risk behaviour, vulnerability, HIV prevalence and interventions, under the headings pastoralists, refugees, IGAD and north-east Africa for the period 2001-2014. Of the 214 documents reviewed, 78 met the inclusion criteria and were included. Most HIV/AIDS related studies focusing of pastoral communities in IGAD countries were found to be limited in scope and coverage but reveal precarious situations. Sero-prevalence among various pastoral populations ranged from 1% to 21% in Ethiopia, Kenya, Somalia and Uganda and from 1% to 5% among refugees in Sudan, Kenya and Uganda. Socioeconomic, cultural, logistic, infrastructure and programmatic factors were found to contribute to continuing vulnerability to HIV. Interventions need to be further contextualised to the needs of those impoverished populations and integrated into national HIV/AIDS programmes. HIV/AIDS remains a major public health concern among the pastoral and refugee communities of IGAD countries. This calls for IGAD to collaborate with national and international partners in designing and implementing more effective prevention and control programmes. Furthermore, interventions must extend beyond the health sector and improve the livelihood of these populations.

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Spatial analysis of factors associated with HIV infection among young people in Uganda, 2011

Cited by 51 publications

References 44 publications

Spatial patterns of HIV prevalence and service use in East Zimbabwe: implications for future targeting of interventions

Spatial patterns of HIV prevalence and service use in East Zimbabwe: implications for future targeting of interventions

Spatial-temporal analysis of pulmonary tuberculosis in the northeast of the Yunnan province, People’s Republic of China

HIV/AIDS among pastoralists and refugees in north-east Africa: a neglected problem

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