Immo Kleinschmidt

Young people's sexual health in South Africa: HIV prevalence and sexual behaviors from a nationally representative household survey

Objectives:To determine the prevalence of HIV infection, HIV risk factors, and exposure to national HIV prevention programs, and to identify factors associated with HIV infection among South African youth, aged 15–24 years. Design:A cross-sectional, nationally representative, household survey. Methods:From March to August 2003 we conducted a national survey of HIV prevalence and sexual behavior among 11 904 15–24 year olds. Multivariable models for HIV infection were restricted to sexually experienced youth. Results:Young women were significantly more likely to be infected with HIV in comparison with young men (15.5 versus 4.8%). Among men, a history of genital ulcers in the past 12 months was associated with HIV infection [adjusted odds ratio (AOR), 1.91; 95% confidence interval (CI), 1.04–3.49) whereas among women a history of unusual vaginal discharge in the past 12 months was associated with HIV infection (AOR, 1.75; 95% CI, 1.26–2.44). Young women with older partners were also at increased risk of HIV infection. Among both men and women, increasing partner numbers and inconsistent condom use were significantly associated with HIV infection. Males and females who reported participation in at least one loveLife program were less likely to be infected with HIV (AOR, 0.60; 95% CI, 0.40–0.89; AOR, 0.61; 95% CI, 0.43–0.85, respectively). Conclusion:This survey confirms the high HIV prevalence among young people in South Africa and, in particular, young womens disproportionate risk. Programs for youth must continue to promote partner reduction, consistent condom use and prompt treatment for sexually transmitted infections while also addressing contextual factors that make it difficult for them to implement behavior change.

Estimation of the burden of active and life-time epilepsy: A meta-analytic approach

Purpose:  To estimate the burden of lifetime epilepsy (LTE) and active epilepsy (AE) and examine the influence of study characteristics on prevalence estimates.

Smoking behaviour can be predicted by neighbourhood deprivation measures.

STUDY OBJECTIVE--To assess whether small area measures of socioeconomic deprivation predict variation in individual smoking behaviour. To examine the adequacy of an individual level statistical model for the analysis of data on groups of individuals who live in the same geographical area. DESIGN--Individual level and two level logistic regression analysis of data on individual smoking from a regional health survey, and neighbourhood deprivation scores for 1991 census wards calculated from 1991 census data. SETTING--The North West Thames Regional Health Authority area. PARTICIPANTS--Random sample of 8,251 adults in North West Thames Regions. MAIN RESULTS--There was a highly significant association between being a smoker and the neighbourhood deprivation score of the area of residence. With the two level model, after allowing for age and sex, the estimated odds ratio of being a smoker for an individual in the highest quintile of deprivation compared with someone in the lowest quintile was 1.52 (95% confidence interval 1.33, 1.74). Results obtained using the individual level model were similar. Variation between wards accounted for around 6% of the total variation in smoking behaviour after neighbourhood deprivation of the ward had been taken into account. Deprivation of the area of residence remained a significant predictor of smoking status even after the socioeconomic group of the individual has been taken into account. CONCLUSIONS--Neighbourhood deprivation of the area of residence is a predictor of smoking status of individuals. In this example the two level model was reasonably well approximated by the individual level model.

Malaria vector control by indoor residual insecticide spraying on the tropical island of Bioko, Equatorial Guinea

BackgroundA comprehensive malaria control intervention was initiated in February 2004 on Bioko Island, Equatorial Guinea. This manuscript reports on the continuous entomological monitoring of the indoor residual spray (IRS) programme during the first two years of its implementation.MethodsMosquitoes were captured daily using window traps at 16 sentinel sites and analysed for species identification, sporozoite rates and knockdown resistance (kdr) using polymerase chain reaction (PCR) to assess the efficacy of the vector control initiative from December 2003 to December 2005.ResultsA total of 2,807 and 10,293 Anopheles funestus and Anopheles gambiae s.l. respectively were captured throughout the study period. Both M and S molecular forms of An. gambiae s.s. and Anopheles melas were identified. Prior to the first round of IRS, sporozoite rates were 6.0, 8.3 and 4.0 for An. gambiae s.s., An. melas and An. funestus respectively showing An. melas to be an important vector in areas in which it occurred. After the third spray round, no infective mosquitoes were identified. After the first spray round using a pyrethroid spray the number of An. gambiae s.s. were not reduced due to the presence of the kdr gene but An funestus and An. melas populations declined from 23.5 to 3.1 and 5.3 to 0.8 per trap per 100 nights respectively. After the introduction of a carbamate insecticide in the second round, An. gambiae s.s. reduced from 25.5 to 1.9 per trap per 100 nights and An. funestus and An. melas remained at very low levels. Kdr was found only in the M-form of An. gambiae s.s. with the highest frequency at Punta Europa (85%).ConclusionAll three vectors that were responsible for malaria transmission before the start of the intervention were successfully controlled once an effective insecticide was used.Continuous entomological surveillance including resistance monitoring is of critical importance in any IRS based malaria vector control programme. This paper demonstrates that sufficient resources for such monitoring should be included in any proposal in order to avoid programme failures.

Identification of hot spots of malaria transmission for targeted malaria control.

BACKGROUND Variation in the risk of malaria within populations is a frequently described but poorly understood phenomenon. This heterogeneity creates opportunities for targeted interventions but only if hot spots of malaria transmission can be easily identified. METHODS We determined spatial patterns in malaria transmission in a district in northeastern Tanzania, using malaria incidence data from a cohort study involving infants and household-level mosquito sampling data. The parasite prevalence rates and age-specific seroconversion rates (SCRs) of antibodies against Plasmodium falciparum antigens were determined in samples obtained from people attending health care facilities. RESULTS Five clusters of higher malaria incidence were detected and interpreted as hot spots of transmission. These hot spots partially overlapped with clusters of higher mosquito exposure but could not be satisfactorily predicted by a probability model based on environmental factors. Small-scale local variation in malaria exposure was detected by parasite prevalence rates and SCR estimates for samples of health care facility attendees. SCR estimates were strongly associated with local malaria incidence rates and predicted hot spots of malaria transmission with 95% sensitivity and 85% specificity. CONCLUSIONS Serological markers were able to detect spatial variation in malaria transmission at the microepidemiological level, and they have the potential to form an effective method for spatial targeting of malaria control efforts.

Exploring 30 years of malaria case data in KwaZulu-Natal South Africa Part II. The impact of non-climatic factors.

Large parts of Africa are prone to malaria epidemics. Advance epidemic warning would give health services an opportunity to prepare. Because malaria transmission is largely limited by climate, climate‐based epidemic warning systems are a real possibility. To develop and test such a system, good long‐term malaria and climate data are needed. In KwaZulu‐Natal (KZN), South Africa, 30 years of confirmed malaria case data provide a unique opportunity to examine short‐ and long‐term trends. We analysed seasonal case totals and seasonal changes in cases (both log‐transformed) against a range of climatic indicators obtained from three weather stations in the highest malaria incidence districts, using linear regression analysis. Seasonal changes in case numbers (delta log cases, dlc) were significantly associated with several climate variables. The two most significant ones were mean maximum daily temperatures from January to October of the preceding season (n = 30, r2 = 0.364, P = 0.0004) and total rainfall during the current summer months of November–March (n = 30, r2 = 0.282, P = 0.003). These two variables, when entered into the same regression model, together explained 49.7% of the total variation in dlc. We found no evidence of association between case totals and climate. In KZN, where malaria control operations are intense, climate appears to drive the interannual variation of malaria incidence, but not its overall level. The accompanying paper provides evidence that overall levels are associated with non‐climatic factors such as drug resistance and possibly HIV prevalence.

Incidence of epilepsy A systematic review and meta-analysis

Objective: To estimate the pooled incidence of epilepsy from published studies and investigate sources of heterogeneity in the estimates. Methods: We searched online databases for incidence studies and used meta-analytic methods to analyze the data. Results: Thirty-three articles met the entry criteria. The median incidence of epilepsy was 50.4/100,000/year (interquartile range [IQR] 33.6–75.6), while it was 45.0 (IQR 30.3–66.7) for high-income countries and 81.7 (IQR 28.0–239.5) for low- and middle-income countries. Population-based studies had higher incidence estimates than hospital-based studies (p = 0.02) while retrospective study design was associated with lower estimates than prospective studies (p = 0.04). Conclusion: We provide data that could potentially be used to assess the burden and analyze the trends in incidence of epilepsy. Our results support the need for large population-based incidence studies of epilepsy.

Prevalence of active convulsive epilepsy in sub-Saharan Africa and associated risk factors: Cross-sectional and case-control studies

Summary Background The prevalence of epilepsy in sub-Saharan Africa seems to be higher than in other parts of the world, but estimates vary substantially for unknown reasons. We assessed the prevalence and risk factors of active convulsive epilepsy across five centres in this region. Methods We did large population-based cross-sectional and case-control studies in five Health and Demographic Surveillance System centres: Kilifi, Kenya (Dec 3, 2007–July 31, 2008); Agincourt, South Africa (Aug 4, 2008–Feb 27, 2009); Iganga-Mayuge, Uganda (Feb 2, 2009–Oct 30, 2009); Ifakara, Tanzania (May 4, 2009–Dec 31, 2009); and Kintampo, Ghana (Aug 2, 2010–April 29, 2011). We used a three-stage screening process to identify people with active convulsive epilepsy. Prevalence was estimated as the ratio of confirmed cases to the population screened and was adjusted for sensitivity and attrition between stages. For each case, an age-matched control individual was randomly selected from the relevant centres census database. Fieldworkers masked to the status of the person they were interviewing administered questionnaires to individuals with active convulsive epilepsy and control individuals to assess sociodemographic variables and historical risk factors (perinatal events, head injuries, and diet). Blood samples were taken from a randomly selected subgroup of 300 participants with epilepsy and 300 control individuals from each centre and were screened for antibodies to Toxocara canis, Toxoplasma gondii, Onchocerca volvulus, Plasmodium falciparum, Taenia solium, and HIV. We estimated odds ratios (ORs) with logistic regression, adjusted for age, sex, education, employment, and marital status. Results 586 607 residents in the study areas were screened in stage one, of whom 1711 were diagnosed as having active convulsive epilepsy. Prevalence adjusted for attrition and sensitivity varied between sites: 7·8 per 1000 people (95% CI 7·5–8·2) in Kilifi, 7·0 (6·2–7·4) in Agincourt, 10·3 (9·5–11·1) in Iganga-Mayuge, 14·8 (13·8–15·4) in Ifakara, and 10·1 (9·5–10·7) in Kintampo. The 1711 individuals with the disorder and 2032 control individuals were given questionnaires. In children (aged <18 years), the greatest relative increases in prevalence were associated with difficulties feeding, crying, or breathing after birth (OR 10·23, 95% CI 5·85–17·88; p<0·0001); abnormal antenatal periods (2·15, 1·53–3·02; p<0·0001); and head injury (1·97, 1·28–3·03; p=0·002). In adults (aged ≥18 years), the disorder was significantly associated with admission to hospital with malaria or fever (2·28, 1·06–4·92; p=0·036), exposure to T canis (1·74, 1·27–2·40; p=0·0006), exposure to T gondii (1·39, 1·05–1·84; p=0·021), and exposure to O volvulus (2·23, 1·56–3·19; p<0·0001). Hypertension (2·13, 1·08–4·20; p=0·029) and exposure to T solium (7·03, 2·06–24·00; p=0·002) were risk factors for adult-onset disease. Interpretation The prevalence of active convulsive epilepsy varies in sub-Saharan Africa and that the variation is probably a result of differences in risk factors. Programmes to control parasitic diseases and interventions to improve antenatal and perinatal care could substantially reduce the prevalence of epilepsy in this region. Funding Wellcome Trust, University of the Witwatersrand, and South African Medical Research Council.

Cancer incidence near municipal solid waste incinerators in Great Britain

By use of the postcoded database held by the Small Area Health Statistic Unit, cancer incidence of over 14 million people living near 72 municipal solid waste incinerators in Great Britain was examined from 1974-86 (England), 1974-84 (Wales) and 1975-87 (Scotland). Numbers of observed cases were compared with expected numbers calculated from national rates (regionally adjusted) after stratification by a deprivation index based on 1981 census small area statistics. Observed-expected ratios were tested for decline in risk with distance up to 7.5 km. The study was conducted in two stages: the first involved a stratified random sample of 20 incinerators; the second the remaining 52 incinerators. Over the two stages of the study was a statistically significant (P<0.05) decline in risk with distance from incinerators for all cancers combined, stomach, colorectal, liver and lung cancer. Among these cancers in the second stage, the excess from 0 to 1 km ranged from 37% for liver cancer (0.95) excess cases 10(-5) per year to 5% for colorectal cancer. There was evidence of residual confounding near the incinerators, which seems to be a likely explanation of the finding for all cancers, stomach and lung, and also to explain at least part of the excess of liver cancer. For this reason and because of a substantial level of misdiagnosis (mainly secondary tumours) found among registrations and death certificates for liver cancer, further investigation, including histological review of the cases, is to be done to help determine whether or not there is an increase in primary liver cancer in the vicinity of incinerators.

An empirical malaria distribution map for West Africa

The objective of this study was to produce a malaria distribution map that would constitute a useful tool for development and health planners in West Africa. The recently created continental database of malaria survey results ( MARA/ARMA 1998 ) provides the opportunity for producing empirical models and maps of malaria distribution at a regional and eventually at a continental level. This paper reports on the mapping of malaria distribution for sub‐Saharan West Africa based on these data. The strategy was to undertake a spatial statistical analysis of malaria parasite prevalence in relation to those potential bio‐physical environmental factors involved in the distribution of malaria transmission intensity which are readily available at any map location. The resulting model was then used to predict parasite prevalence for the whole of West Africa. We also produced estimates of the proportion of population of each country in the region exposed to various categories of risk to show the impact that malaria is having on individual countries. The data represent a very large sample of children in West Africa. It constitutes a first attempt to produce a malaria risk map of the West African region, based entirely on malariometric data. We anticipate that it will provide useful additional guidance to control programme managers, and that it can be refined once sufficient additional data become available.