Ayles, H

Cambiano, V

Chilongosi, R

Corbett, E

Fielding, K

Hatzold, K

Hensen, B

Indravudh, P

Johnson, C

Nalubamba, M

Neuman, M

Wilson, E

English

UCL Discovery

17.7% 16.2%11.4%25.6% 26.5%15.9% 16.8%20.8%17.8% 17.3%2.8% 2.3% 2.2%4.3% 4.3%1.8%2.8%4.1%2.7%3.6%All Female - noHIVSTMale - noHIVSTFemale -has HIVSTMale - hasHIVSTLowest Second Highest Verygood/goodFair/poorFrequent tester (3-4 tests/year) Very freq. tester (5+ tests/year)Self-reported healthAssets indexM Neuman, V Cambiano, C Johnson, R Chilongosi, K Fielding, K Hatzold, B Hensen, P Indravudh, M Nalubamba, E Wilson, H Ayles, EL Corbett. BACKGROUND As countries approach the “First 90” of UN 90-90-90 targets, HIV testing will become increasingly less efficient, and excessive use of HIV testing among low risk populations is an increasing concern. Here, we investigate frequent testing in general populations in Malawi and Zambia during 2 community-based HIV self-testing (CB-HIVST) trials. METHODSIn Malawi and Zambia, 22 and 12 clinic catchment areas, respectively, were randomized to receive 12 months of CB-HIVST or standard clinic-based services, followed by endline household surveys. Surveys were conducted in October 2017-Feburary 2018, with self-reported HIV prevalence of 16.0% in Malawi and 6.8% in Zambia. The following definitions were based on self-reported HIV testing in the past 12 months: recent testers (1-2 tests), frequent testers (3-4 tests), and very frequent testers (5+ tests). Multinomial logistic regression with standard errors adjusted for clustering was used to investigate associations between study arm, sex, and other socio-demographic and health-related indicators with frequent and very frequent testing. Effect modification by country and sex was also assessed. Missing data were imputed using chained multiple imputation models. RESULTSOf 10,368 respondents with complete testing data, 6,273 tested for HIV at least once in the past 12 months. These included 1,111 (17.7%) frequent testers and 179 (2.8%) very frequent testers (table). Frequent testing was associated with the highest household wealth tertile (adjusted OR [AOR]: 1.47; 95% confidence interval [CI]: 1.09, 1.99), and with HIVST use (AOR men: 2.95; 95%CI: 2.37, 3.69; women: 1.88; 95%CI: 1.47, 2.40; interaction p=0.001). Too much of a good thing? Prevalence and determinants of frequent and very frequent HIV testing in Zambia and MalawiCONCLUSIONFrequent testing was common and associated with greater likelihood of HIVST uptake from both men and women, and with wealthier households.  Very frequent testing was a potential marker of ill-health, being associated with poorer self-rated health. Risk behaviours were not fully measured in this study, so it is not clear whether testers were testing in response to perceived risk or for other reasons.CONTACTMelissa Neuman, ScD MSLondon School of Hygiene and Tropical MedicineMelissa.Neuman@lshtm.ac.ukWHO guidelines for high HIV prevalence settings encourage annual testing for adults, and testing up to 2-3 times per year for key populations depending on risk. As HIV testing and HIV self-testing scale-up, efforts are needed to optimize implementation by minimizing inefficient testing while promoting HIV testing for those at increased risk of infection.Missing data in the following covariates: educational attainment (n=2), self-testing status (n=230), self-reported health (n=10), sexual behaviour (n=137), assets tertile (n=819). Table. Less frequent, frequent, and very frequent testing by respondent characteristicsFigure. Predicted probabilities of frequent or very frequent HIV testing by gender, HIVST use, household assets, and self-reported healthResults mutually adjusted, and also adjusted for age, educational attainment, having a biological child, country, and study arm. Standard errors adjusted for clustered study design using the vce(cluster) of mlogit in Stata 15.0. Missing data imputed using chained imputation models. Less frequent testers(1-2 tests/yr., N=4,983)Frequent testers(3-4 tests/yr., N=1,111)Very frequent testers(5+ tests/yr., N=179)Totaln Col. % n Col. % n Col. % n Col. %Socio-demographics and self-testingAge16-19 yrs. 699 14 118 10.6 23 12.8 840 13.420-24 yrs. 1,020 20.5 265 23.9 56 31.3 1,341 21.425-29 yrs. 821 16.5 212 19.1 34 19 1,067 1730-39 yrs. 1,150 23.1 293 26.4 41 22.9 1,484 23.740 yrs. and older 1,293 25.9 223 20.1 25 14 1,541 24.6Male gender 1,885 37.8 365 32.9 58 32.4 2,308 36.8Self-tested in prior 12 months 1,076 22.5 460 41.4 79 44.1 1,615 26.6Educational attainmentNo formal schooling 487 9.8 105 9.5 18 10.1 610 9.7Primary incomplete or complete 2,859 57.4 674 60.7 104 58.1 3,637 58Secondary or higher 1,635 32.8 332 29.9 57 31.8 2,024 32.3Health and reproductive historyHas a biological child 4,009 80.5 966 86.9 159 88.8 5,134 81.8Self-reported health fair or poor 849 17.1 167 15 32 17.9 1,048 16.7Sexual behaviour with steady partnersNo partner in past 3 months 1,727 37.8 326 31.8 39 22.5 2,092 36.2Condom always 1,556 34 308 30 55 31.8 1,919 33.2Condom sometimes or never 1,290 28.2 392 38.2 79 45.7 1,761 30.5Household attributesAssets indexLowest tertile 1,727 37.8 326 31.8 39 22.5 2,092 36.2Second tertile 1,556 34 308 30 55 31.8 1,919 33.2Highest tertile 1,290 28.2 392 38.2 79 45.7 1,761 30.5OtherIntervention arm 2,592 52 678 61 120 67 3,390 54CountryMalawi 2,390 48 699 62.9 106 59.2 3,195 50.9Zambia 2,593 52 412 37.1 73 40.8 30,78 49.1Very frequent testing was associated with highest wealth tertile (AOR: 2.60; 95%CI: 1.40, 4.85), HIVST (AOR: 2.23; 95%CI: 1.29, 3.85 – no gender difference), and marginally associated with fair or poor self-rated health (AOR: 1.35; 95%CI: 0.98, 1.86) (Figure). There was weak evidence of an association between frequent and very frequent testing and sexual behaviour (AOR for very frequent testing condom users compared to persons with no partner: 1.53, 95% CI: 0.92, 2.55) (data not shown). 

Too much of a good thing? Prevalence and determinants of frequent HIV testing in Zambia and Malawi

https://discovery.ucl.ac.uk/id/eprint/10085787/1/too-much-of-a-good-thing.pdf

Too much of a good thing? Prevalence and determinants of frequent HIV testing in Zambia and Malawi

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