Hot-spots Clusters of HIV Infection in Cameroon: Space-time Analysis from the Demographic and Health Surveys

Abstract Background : The Human Immunodeficiency Virus(HIV) infection prevalence in Cameroon has consecutively decreased from 5.28% in 2004 to 2.8% in 2018. However , this total decrease in prevalence may hide some disparities especially in terms of spatial or geographical pattern. Efficient control and fighting against HIV infection requires to target hotspot areas . This study was aimed to investigate whether there is a spatial pattern of HIV in Cameroon and to determine the hot-spots clusters .Methods : HIV biomarkers data with Global Positioning System (GPS) location data were leveraged from the Cameroon 2004, 2011, and 2018 Demographic and Health Survey ( DHS ) after an approved request from the MEASURES Demographic and Health Survey Program . The spatial autocorrelation test was performed with the Moran I test through the R package " DCluster ". The discrete Poisson model was fitted to scan and detect hot-spots clusters based on the Kulldorff test with the SaTScan software version 9.4, with purely spatial and space -time analysis respectively . Finally , the data and detected clusters were imported to QGIS software version 3.20.2 for maps manipulations.Results : For the three considered periods of 2004, 2011, and 2018 respectively , there was a spatial autocorrelation of HIV infection in Cameroon . A total of 3, 5, and 2 significant hot-spots clusters were detected for the periods of 2004, 2011, and 2018 respectively . In the prospective space -time analysis , 2 significant clusters have been detected from 2004 to 2018. The relative- risk in the significant detected clusters were 2.72 (p-value =0.001 ) and 3.37 (p-value= 0.026) respectively . Cluster 1 included the following subdivisions : Mefou et Afamba , Nyong et So'o , Nyong et Mfoumou , Haute Sanaga , Mvila , Dja et lobo , Haut- Nyong , Boumba et Ngoko ; Kadey , Lom et Djerem , and Mbere . The other cluster included : Nkam , Sanaga -Maritime, and Nyong - Ekele .Conclusion : Despite the decrease of HIV epidemiology in Cameroon , the study revealed that there is a spatial pattern of HIV in Cameroon and the hot-spots clusters were detected . In its effort to eliminate HIV infection by 2030 in Cameroon , the public health policies should target more of the detected HIV hot-spots clusters in this study while maintaining effective control in other parts of the country which are cold -spots.