| Literature DB >> 22611485 |
Reuben Granich1, Nicolas Muraguri, Alexandre Doyen, Navneet Garg, Brian G Williams.
Abstract
In 2009, Government of Kenya with key stakeholders implemented an integrated multi-disease prevention campaign for water-borne diseases, malaria and HIV in Kisii District, Nyanza Province. The three day campaign, targeting 5000 people, included testing and counseling (HTC), condoms, long-lasting insecticide-treated bednets, and water filters. People with HIV were offered on-site CD4 cell counts, condoms, co-trimoxazole, and HIV clinic referral. We analysed the CD4 distributions from a district hospital cohort, campaign participants and from the 2007 Kenya Aids Indicator Survey (KAIS). Of the 5198 individuals participating in the campaign, all received HTC, 329 (6.3%) tested positive, and 255 (5%) were newly diagnosed (median CD4 cell count 536 cells/μL). The hospital cohort and KAIS results included 1,284 initial CD4 counts (median 348/L) and 306 initial CD4 counts (median 550/μL), respectively (campaign and KAIS CD4 distributions P = 0.346; hospital cohort distribution was lower P < 0.001 and P < 0.001). A Nyanza Province campaign strategy including ART <350 CD4 cell count could avert approximately 35,000 HIV infections and 1,240 TB cases annually. Community-based integrated public health campaigns could be a potential solution to reach universal access and Millennium Development Goals.Entities:
Year: 2012 PMID: 22611485 PMCID: PMC3352252 DOI: 10.1155/2012/412643
Source DB: PubMed Journal: AIDS Res Treat ISSN: 2090-1240
Figure 1Map of Kenya showing Kisii, Nyanza Province, and inset showing the location of the three campaign sites and Kisii Level 5 Hospital (Kisii Town).
Figure 2Comparison of the CD4 cell count distribution in Nyanza Province (red; KAIS survey) and the Kisii Hospital cohort (blue). The data for the hospital cohort are scaled to match the KAIS data for the lowest CD4 cell count range and the differences in the heights of the bars for the higher ranges show the proportion that are missed in the hospital cohort.
CD 4 values from the campaign, hospital reference, and KAIS data sets. The table gives N, the number of people for whom a CD4 cell count was done, the median CD4 cell count, and the proportion of those tested that are below 250, 350, and 500 cells/μL. Numbers in brackets are percentages. Using a Kolmogorov-Smirnov test, The CD4 cell count distribution for the Hospital Reference data set is significantly different from the other two (P < 0.001 in both cases) but the Campaign and KAIS data sets are not significantly different (P = 0.346).
| Campaign | Hospital reference | Nyanza KAIS | |
|---|---|---|---|
|
| 255 | 1284 | 306 |
|
| |||
| Median/ | 536 | 348 | 550 |
|
| 33 (13%) | 436 (34%) | 52 (17%) |
|
| 64 (25%) | 642 (50%) | 92 (30%) |
|
| 112 (44%) | 899 (70%) | 141 (46%) |
|
| |||
|
| 187 (74%) | 1137 (89%) | 220 (72%) |
|
| |||
|
| 228 (90%) | 1215 (95%) | 258 (84%) |
Projected prevention impact of campaign approach by CD4 eligibility criteria for Nyanza Province.
| Campaign approach | Passive case-finding | |||||||
|---|---|---|---|---|---|---|---|---|
| CD4 cell count at start of treatment (/ | HIV-positive population started on ART (%) | Number started on ART (thousands) | HIV infections averted per year (thousands) | TB cases averted per year | HIV-positive population started on ART (%) | Number started on ART (thousands) | HIV infections averted per year (thousands) | TB cases averted per year |
|
| 13 | 38 | 13 | 645 | 13 | 38 | 13 | 645 |
|
| 25 | 74 | 35 | 1240 | 19 | 56 | 26 | 942 |
|
| 44 | 129 | 86 | 2182 | 27 | 79 | 53 | 1339 |
| Immediate | 100 | 294 | 294 | 4959 | 38 | 112 | 112 | 1884 |