Predictors of health workers' knowledge about artesunate-based severe malaria treatment recommendations in government and faith-based hospitals in Kenya.

BACKGROUND: Health workers' knowledge deficiencies about artesunate-based severe malaria treatment recommendations have been reported. However, predictors of the treatment knowledge have not been examined. In this paper, predictors of artesunate-based treatment knowledge among inpatient health workers in two hospital sectors in Kenya are reported. METHODS: Secondary analysis of 367 and 330 inpatient health workers randomly selected and interviewed at 47 government hospitals in 2016 and 43 faith-based hospitals in 2017 respectively, was undertaken. Multilevel ordinal and binary logistic regressions examining the effects of 11 factors on five knowledge outcomes in government and faith-based hospital sectors were performed. RESULTS: Among respective government and faith-based health workers, about a third of health workers had high knowledge of artesunate treatment policies (30.8% vs 32.9%), a third knew all dosing intervals (33.5% vs 33.3%), about half knew preparation solutions (49.9% vs 55.8%), half to two-thirds knew artesunate dose for both weight categories (50.8% vs 66.7%) and over three-quarters knew the preferred route of administration (78.7% vs 82.4%). Eight predictors were significantly associated with at least one of the examined knowledge outcomes. In the government sector, display of artesunate administration posters, paediatric ward allocation and repeated surveys were significantly associated with more than one of the knowledge outcomes. In the faith-based hospitals, availability of artesunate at hospitals and health worker pre-service training were associated with multiple outcomes. Exposure to in-service malaria case-management training and access to malaria guidelines were only associated with higher knowledge about artesunate treatment policy. CONCLUSION: Programmatic interventions ensuring display of artesunate administration posters in the wards, targeting of health workers managing adult patients in the medical wards, and repeated knowledge assessments are likely to be beneficial for improving the knowledge of government health workers about artesunate-based severe malaria treatment recommendations. The availability of artesunate and focus on improvements of nurses' knowledge should be prioritized at the faith-based hospitals.

Time series non-Gaussian Bayesian bivariate model applied to data on HMPV and RSV: a case of Dadaab in Kenya.

BACKGROUND: Human metapneumovirus (HMPV) have similar symptoms to those caused by the respiratory syncytial virus (RSV). The modes of transmission and dynamics of time series data still remain poorly understood. Climatic factors have long been suspected to be implicated in impacting on the number of cases for these epidemics. Currently, only a few models satisfactorily capture the dynamics of time series data of these two viruses. Our objective was to assess the presence of influence of high incidences between the viruses and to ascertain whether higher incidences of one virus are influenced by the other. METHODS: In this study, we used a negative binomial model to investigate the relationship between RSV and HMPV while adjusting for climatic factors. We specifically aimed at establishing the heterogeneity in the autoregressive effect to account for the influence between these viruses. RESULTS: In this study, our findings showed that RSV incidence contributed to the severity of HMPV incidence. This was achieved through comparison of 12 models with different structures, including those with and without interaction between climatic factors. The models with climatic factors out-performed those without. CONCLUSIONS: The study has improved our understanding of the dynamics of RSV and HMPV in relation to climatic cofactors thereby setting a platform to devise better intervention measures to combat the epidemics. We conclude that preventing and controlling RSV infection subsequently reduces the incidence of HMPV.

Understanding the determinants of under-five child mortality in Uganda including the estimation of unobserved household and community effects using both frequentist and Bayesian survival analysis approaches.

BACKGROUND: Infant and child mortality rates are among the health indicators of importance in a given community or country. It is the fourth millennium development goal that by 2015, all the United Nations member countries are expected to have reduced their infant and child mortality rates by two-thirds. Uganda is one of those countries in Sub-Saharan Africa with high infant and child mortality rates, therefore it is important to use sound statistical methods to determine which factors are strongly associated with child mortality which in turn will help inform the design of intervention strategies METHODS: The Uganda Demographic Health Survey (UDHS) funded by USAID, UNFPA, UNICEF, Irish Aid and the United Kingdom government provides a data set which is rich in information on child mortality or survival. Survival analysis techniques are among the well-developed methods in Statistics for analysing time to event data. These methods were adopted in this paper to examine factors affecting under-five child mortality rates (UMR) in Uganda using the UDHS data for 2011 in R and STATA software. RESULTS: Results obtained by fitting the Cox-proportional hazard model with frailty effects and drawing inference using both the frequentists and Bayesian approaches at 5 % significance level, show evidence of the existence of unobserved heterogeneity at the household level but there was not enough evidence to conclude the existence of unobserved heterogeneity at the community level. Sex of the household head, sex of the child and number of births in the past one year were found to be significant. The results further suggest that over the period of 1990-2015, Uganda reduced its UMR by 52 % . CONCLUSION: Uganda has not achieved the MDG4 target but the 52 % reduction in the UMR is a move in the positive direction. Demographic factors (sex of the household head) and Biological determinants (sex of the child and number of births in the past one year) are strongly associated with high UMR. Heterogeneity or unobserved covariates were found to be significant at the household but insignificant at the community level.

Individual and contextual determinants of adequate maternal health care services in Kenya.

This study aimed to examine individual and community level factors associated with adequate use of maternal antenatal health services in Kenya. Individual and community level factors associated with adequate use of maternal health care (MHC) services were obtained from the 2008-09 Kenya Demographic and Health Survey data set. Multilevel partial-proportional odds logit models were fitted using STATA 13.0 to quantify the relations of the selected covariates to adequate MHC use, defined as a three-category ordinal variable. The sample consisted of 3,621 women who had at least one live birth in the five-year period preceding this survey. Only 18 percent of the women had adequate use of MHC services. Greater educational attainment by the woman or her partner, higher socioeconomic status, access to medical insurance coverage, and greater media exposure were the individual-level factors associated with adequate use of MHC services. Greater community ethnic diversity, higher community-level socioeconomic status, and greater community-level health facility deliveries were the contextual-level factors associated with adequate use of MHC. To improve the use of MHC services in Kenya, the government needs to design and implement programs that target underlying individual and community level factors, providing focused and sustained health education to promote the use of antenatal, delivery, and postnatal care.

Spatial modelling and mapping of female genital mutilation in Kenya.

BACKGROUND: Female genital mutilation/cutting (FGM/C) is still prevalent in several communities in Kenya and other areas in Africa, as well as being practiced by some migrants from African countries living in other parts of the world. This study aimed at detecting clustering of FGM/C in Kenya, and identifying those areas within the country where women still intend to continue the practice. A broader goal of the study was to identify geographical areas where the practice continues unabated and where broad intervention strategies need to be introduced. METHODS: The prevalence of FGM/C was investigated using the 2008 Kenya Demographic and Health Survey (KDHS) data. The 2008 KDHS used a multistage stratified random sampling plan to select women of reproductive age (15-49 years) and asked questions concerning their FGM/C status and their support for the continuation of FGM/C. A spatial scan statistical analysis was carried out using SaTScan™ to test for statistically significant clustering of the practice of FGM/C in the country. The risk of FGM/C was also modelled and mapped using a hierarchical spatial model under the Integrated Nested Laplace approximation approach using the INLA library in R. RESULTS: The prevalence of FGM/C stood at 28.2% and an estimated 10.3% of the women interviewed indicated that they supported the continuation of FGM. On the basis of the Deviance Information Criterion (DIC), hierarchical spatial models with spatially structured random effects were found to best fit the data for both response variables considered. Age, region, rural-urban classification, education, marital status, religion, socioeconomic status and media exposure were found to be significantly associated with FGM/C. The current FGM/C status of a woman was also a significant predictor of support for the continuation of FGM/C. Spatial scan statistics confirm FGM clusters in the North-Eastern and South-Western regions of Kenya (p<0.001). CONCLUSION: This suggests that the fight against FGM/C in Kenya is not yet over. There are still deep cultural and religious beliefs to be addressed in a bid to eradicate the practice. Interventions by government and other stakeholders must address these challenges and target the identified clusters.

HIV risk behaviour, viraemia, and transmission across HIV cascade stages including low-level viremia: Analysis of 14 cross-sectional population-based HIV Impact Assessment surveys in sub-Saharan Africa.

As antiretroviral treatment (ART) coverage for people living with HIV (PLHIV) increases, HIV programmes require up-to-date information about evolving HIV risk behaviour and transmission risk, including those with low-level viremia (LLV; >50 to ≤1000 copies/mL), to guide prevention priorities. We aimed to assess differences in sexual risk behaviours, distribution of viral load (VL) and proportion of transmission across PLHIV subgroups. We analysed data from Population-based HIV Impact Assessment surveys in 14 sub-Saharan African countries during 2015-2019. We estimated adjusted prevalence ratios (aPR) of self-reported HIV high-risk behaviour (multiple partners and condomless sex) across cascade stages via generalised estimation equations. We modelled the proportions of transmission from each subgroup using relative self-reported sexual risk, a Hill function for transmission rate by VL, and proportions within cascade stages from surveys and UNAIDS country estimates for 2010-2020. Compared to PLHIV with undetectable VL (≤50 copies/mL), undiagnosed PLHIV (aPR women: 1.28 [95% CI: 1.08-1.52]; men: 1.61 [1.33-1.95]) and men diagnosed but untreated (2.06 [1.52-2.78]) were more likely to self-report high-risk sex. High-risk behaviour was not significantly associated with LLV. Mean VL was similar among undiagnosed, diagnosed but untreated, and on ART but non-suppressed sub-groups. Across surveys, undiagnosed and diagnosed but untreated contributed most to transmission (40-91% and 1-41%, respectively), with less than 1% from those with LLV. Between 2010 and 2020, the proportion of transmission from individuals on ART but non-suppressed increased. In settings with high ART coverage, effective HIV testing, ART linkage, and retention remain priorities to reduce HIV transmission. Persons with LLV are an increasing share of PLHIV but their contribution to HIV transmission was small. Improving suppression among PLHIV on ART with VL ≥1000 copies/mL will become increasingly important.

Factors associated with hospital length of stay in patients admitted with suspected malaria in Kenya: secondary analysis of a cross-sectional survey.

OBJECTIVES: To investigate factors associated with hospital length of stay (LOS) in patients admitted with suspected malaria using a competing risk approach. SETTING: County government referrals and major faith-based hospitals in Kenya in 2018. DESIGN: Secondary analysis of a cross-sectional survey data. PARTICIPANTS: Data were extracted from 2396 medical records of patients admitted with suspected malaria at 90 hospitals. OUTCOME MEASURES: LOS, defined as time to discharge, was the primary event of interest, and time to death was the competing event against patient factors assessed during admission and hospitalisation. RESULTS: Among the patients analysed, 2283 were discharged, 49 died and 64 were censored. The median LOS was 4 days (IQR: 3-6 days). The cumulative incidence of discharge significantly decreased (p<0.05) by 12.7% (subdistribution-HR (SDHR): 0.873; 95% CI 0.789 to 0.967) when the respiratory rate was assessed, by 14.1% (SDHR 0.859; 95% CI 0.754 to 0.978) when oxygen saturation was monitored, by 23.1% (SDHR 0.769; 95% CI 0.709 to 0.833) and 23.4% (SDHR 0.766; 95% CI 0.704 to 0.833) when haemoglobin/haematocrit and glucose/random blood sugar were performed, respectively, and by 30.4% (SDHR 0.696; 95% CI 0.626 to 0.774) when patients had at least one clinical feature of severe malaria. Conversely, patients with confirmed severe malaria and those treated with injectable artesunate had a significantly increased cumulative incidence of discharge by 21.4% (SDHR 1.214; 95% CI 1.082 to 1.362) and 33.9% (SDHR 1.339; 95% CI 1.184 to 1.515), respectively. CONCLUSIONS: Factors of inpatient clinical processes that influence hospital LOS were identified. These can be targeted during quality improvement interventions to enhance health service delivery in Kenya. Early recognition and appropriate management of the signs of malaria severity could greatly affect beneficial outcomes. Strengthening clinical practices and nursing care according to national case management guidelines should be a priority for malaria control managers in Kenya.

Where Are the Newly Diagnosed HIV Positives in Kenya? Time to Consider Geo-Spatially Guided Targeting at a Finer Scale to Reach the "First 90".

Background: The UNAIDS 90-90-90 Fast-Track targets provide a framework for assessing coverage of HIV testing services (HTS) and awareness of HIV status - the "first 90." In Kenya, the bulk of HIV testing targets are aligned to the five highest HIV-burden counties. However, we do not know if most of the new HIV diagnoses are in these five highest-burden counties or elsewhere. Methods: We analyzed facility-level HTS data in Kenya from 1 October 2015 to 30 September 2016 to assess the spatial distribution of newly diagnosed HIV-positives. We used the Moran's Index (Moran's I) to assess global and local spatial auto-correlation of newly diagnosed HIV-positive tests and Kulldorff spatial scan statistics to detect hotspots of newly diagnosed HIV-positive tests. For aggregated data, we used Kruskal-Wallis equality-of-populations non-parametric rank test to compare absolute numbers across classes. Results: Out of 4,021 HTS sites, 3,969 (98.7%) had geocodes available. Most facilities (3,034, 76.4%), were not spatially autocorrelated for the number of newly diagnosed HIV-positives. For the rest, clustering occurred as follows; 438 (11.0%) were HH, 66 (1.7%) HL, 275 (6.9%) LH, and 156 (3.9%) LL. Of the HH sites, 301 (68.7%) were in high HIV-burden counties. Over half of 123 clusters with a significantly high number of newly diagnosed HIV-infected persons, 73(59.3%) were not in the five highest HIV-burden counties. Clusters with a high number of newly diagnosed persons had twice the number of positives per 1,000,000 tests than clusters with lower numbers (29,856 vs. 14,172). Conclusions: Although high HIV-burden counties contain clusters of sites with a high number of newly diagnosed HIV-infected persons, we detected many such clusters in low-burden counties as well. To expand HTS where most needed and reach the "first 90" targets, geospatial analyses and mapping make it easier to identify and describe localized epidemic patterns in a spatially dispersed epidemic like Kenya's, and consequently, reorient and prioritize HTS strategies.

Spatial and socio-economic correlates of effective contraception among women seeking post-abortion care in healthcare facilities in Kenya.

INTRODUCTION: Information, counseling, availability of contraceptives, and their adoption by post-abortion care (PAC) patients are central to the quality of PAC in healthcare facilities. Effective contraceptive adoption by these patients reduces the risks of unintended pregnancy and repeat abortion. METHODS: This study uses data from the Incidence and Magnitude of Unsafe Abortion Study of 2012 to assess the level and determinants of highly effective contraception among patients treated with complications from an unsafe abortion in healthcare facilities in Kenya. Highly effective contraception was defined as any method adopted by a PAC patient that reduces pregnancy rate by over 99%. RESULTS: Generally, contraceptive counseling was high among all PAC patients (90%). However, only 54% of them received a modern family planning method-45% a short-acting method and 9% a long-acting and permanent method. Adoption of highly effective contraception was determined by patient's previous exposure to unintended pregnancies, induced abortion and modern family planning (FP). Facility level factors associated with the uptake of highly effective contraceptives included: facility ownership, availability of evacuation procedure room, whether the facility had a specialized obstetric-gynecologist, a facility that also had maternity services and the number of FP methods available for PAC patients. DISCUSSION AND CONCLUSION: For better adoption of highly effective FP, counseling of PAC patients requires an understanding of the patient's past experience with contraception and their future fertility intentions and desires in order to meet their reproductive needs more specifically. Family planning integration with PAC can increase contraceptive uptake and improve the reproductive health of post-abortion care patients.

Finding Hidden HIV Clusters to Support Geographic-Oriented HIV Interventions in Kenya.

BACKGROUND: In a spatially well known and dispersed HIV epidemic, identifying geographic clusters with significantly higher HIV prevalence is important for focusing interventions for people living with HIV (PLHIV). METHODS: We used Kulldorff spatial-scan Poisson model to identify clusters with high numbers of HIV-infected persons 15-64 years old. We classified PLHIV as belonging to either higher prevalence or lower prevalence (HP/LP) clusters, then assessed distributions of sociodemographic and biobehavioral HIV risk factors and associations with clustering. RESULTS: About half of survey locations, 112/238 (47%) had high rates of HIV (HP clusters), with 1.1-4.6 times greater PLHIV adults observed than expected. Richer persons compared with respondents in lowest wealth index had higher odds of belonging to a HP cluster, adjusted odds ratio (aOR) 1.61 [95% confidence interval (CI): 1.13 to 2.3], aOR 1.66 (95% CI: 1.09 to 2.53), aOR 3.2 (95% CI: 1.82 to 5.65), and aOR 2.28 (95% CI: 1.09 to 4.78) in second, middle, fourth, and highest quintiles, respectively. Respondents who perceived themselves to have greater HIV risk or were already HIV-infected had higher odds of belonging to a HP cluster, aOR 1.96 (95% CI: 1.13 to 3.4) and aOR 5.51 (95% CI: 2.42 to 12.55), respectively; compared with perceived low risk. Men who had ever been clients of female sex worker had higher odds of belonging to a HP cluster than those who had never been, aOR 1.47 (95% CI: 1.04 to 2.08); and uncircumcised men vs circumcised, aOR 3.2 (95% CI: 1.74 to 5.8). CONCLUSIONS: HIV infection in Kenya exhibits localized geographic clustering associated with sociodemographic and behavioral factors, suggesting disproportionate exposure to higher HIV risk. Identification of these clusters reveals the right places for targeting priority-tailored HIV interventions.

Spatial-temporal trend for mother-to-child transmission of HIV up to infancy and during pre-Option B+ in western Kenya, 2007-13.

INTRODUCTION: Using spatial-temporal analyses to understand coverage and trends in elimination of mother-to-child transmission of HIV (e-MTCT) efforts may be helpful in ensuring timely services are delivered to the right place. We present spatial-temporal analysis of seven years of HIV early infant diagnosis (EID) data collected from 12 districts in western Kenya from January 2007 to November 2013, during pre-Option B+ use. METHODS: We included in the analysis infants up to one year old. We performed trend analysis using extended Cochran-Mantel-Haenszel stratified test and logistic regression models to examine trends and associations of infant HIV status at first diagnosis with: early diagnosis (<8 weeks after birth), age at specimen collection, infant ever having breastfed, use of single dose nevirapine, and maternal antiretroviral therapy status. We examined these covariates and fitted spatial and spatial-temporal semiparametric Poisson regression models to explain HIV-infection rates using R-integrated nested Laplace approximation package. We calculated new infections per 100,000 live births and used Quantum GIS to map fitted MTCT estimates for each district in Nyanza region. RESULTS: Median age was two months, interquartile range 1.5-5.8 months. Unadjusted pooled positive rate was 11.8% in the seven-years period and declined from 19.7% in 2007 to 7.0% in 2013, p < 0.01. Uptake of testing ≤8 weeks after birth was under 50% in 2007 and increased to 64.1% by 2013, p < 0.01. By 2013, the overall standardized MTCT rate was 447 infections per 100,000 live births. Based on Bayesian deviance information criterion comparisons, the spatial-temporal model with maternal and infant covariates was best in explaining geographical variation in MTCT. DISCUSSION: Improved EID uptake and reduced MTCT rates are indicators of progress towards e-MTCT. Cojoined analysis of time and covariates in a spatial context provides a robust approach for explaining differences in programmatic impact over time. CONCLUSION: During this pre-Option B+ period, the prevention of mother to child transmission program in this region has not achieved e-MTCT target of ≤50 infections per 100,000 live births. Geographical disparities in program achievements may signify gaps in spatial distribution of e-MTCT efforts and could indicate areas needing further resources and interventions.

Child mortality inequalities across Rwanda districts: a geoadditive continuous-time survival analysis.

Child survival programmes are efficient when they target the most significant and area-specific factors. This study aimed to assess the key determinants and spatial variation of child mortality at the district level in Rwanda. Data from the 2010 Rwanda Demographic and Health Survey were analysed for 8817 live births that occurred during five years preceding the survey. Out of the children born, 433 had died before survey interviews were carried out. A full Bayesian geo-additive continuous-time hazard model enabled us to maximise data utilisation and hence improve the accuracy of our estimates. The results showed substantial district- level spatial variation in childhood mortality in Rwanda. District-specific spatial characteristics were particularly associated with higher death hazards in two districts: Musanze and Nyabihu. The model estimates showed that there were lower death rates among children from households of medium and high economic status compared to those from low-economic status households. Factors, such as four antenatal care visits, delivery at a health facility, prolonged breastfeeding and mothers younger than 31 years were associated with lower child death rates. Long preceding birth intervals were also associated with fewer hazards. For these reasons, programmes aimed at reducing child mortality gaps between districts in Rwanda should target maternal factors and take into consideration district-specific spatial characteristics. Further, child survival gains require strengthening or scaling-up of existing programmes pertaining to access to, and utilisation of maternal and child health care services as well as reduction of the household gap in the economic status.

Reprint of "Modelling the influence of temperature and rainfall on malaria incidence in four endemic provinces of Zambia using semiparametric Poisson regression".

Although malaria morbidity and mortality are greatly reduced globally owing to great control efforts, the disease remains the main contributor. In Zambia, all provinces are malaria endemic. However, the transmission intensities vary mainly depending on environmental factors as they interact with the vectors. Generally in Africa, possibly due to the varying perspectives and methods used, there is variation on the relative importance of malaria risk determinants. In Zambia, the role climatic factors play on malaria case rates has not been determined in combination of space and time using robust methods in modelling. This is critical considering the reversal in malaria reduction after the year 2010 and the variation by transmission zones. Using a geoadditive or structured additive semiparametric Poisson regression model, we determined the influence of climatic factors on malaria incidence in four endemic provinces of Zambia. We demonstrate a strong positive association between malaria incidence and precipitation as well as minimum temperature. The risk of malaria was 95% lower in Lusaka (ARR=0.05, 95% CI=0.04-0.06) and 68% lower in the Western Province (ARR=0.31, 95% CI=0.25-0.41) compared to Luapula Province. North-western Province did not vary from Luapula Province. The effects of geographical region are clearly demonstrated by the unique behaviour and effects of minimum and maximum temperatures in the four provinces. Environmental factors such as landscape in urbanised places may also be playing a role.

Effect of climate on incidence of respiratory syncytial virus infections in a refugee camp in Kenya: A non-Gaussian time-series analysis.

Respiratory syncytial virus (RSV) is one of the major causes of acute lower respiratory tract infections (ALRTI) in children. Children younger than 1 year are the most susceptible to RSV infection. RSV infections occur seasonally in temperate climate regions. Based on RSV surveillance and climatic data, we developed statistical models that were assessed and compared to predict the relationship between weather and RSV incidence among refugee children younger than 5 years in Dadaab refugee camp in Kenya. Most time-series analyses rely on the assumption of Gaussian-distributed data. However, surveillance data often do not have a Gaussian distribution. We used a generalized linear model (GLM) with a sinusoidal component over time to account for seasonal variation and extended it to a generalized additive model (GAM) with smoothing cubic splines. Climatic factors were included as covariates in the models before and after timescale decompositions, and the results were compared. Models with decomposed covariates fit RSV incidence data better than those without. The Poisson GAM with decomposed covariates of climatic factors fit the data well and had a higher explanatory and predictive power than GLM. The best model predicted the relationship between atmospheric conditions and RSV infection incidence among children younger than 5 years. This knowledge helps public health officials to prepare for, and respond more effectively to increasing RSV incidence in low-resource regions or communities.

A cross-sectional analysis of Kenyan postabortion care services using a nationally representative sample.

OBJECTIVE: To assess quality of postabortion care (PAC) offered by Kenyan healthcare facilities. METHODS: A cross-sectional survey was conducted using data from the Incidence and Magnitude of Unsafe Abortions study, conducted among 326 PAC-providing healthcare facilities throughout Kenya from March 13 to June 30, 2012. Descriptive results with weighted proportions and an ordered probit model were used. RESULTS: Overall, 408 (41.8%) first-trimester PAC cases were treated using appropriate technology versus 826 (82.6%) second-trimester cases. Private healthcare facilities lagged behind public healthcare facilities on the use of appropriate technology: 264 (47.5%) public and 144 (33.1%) private facilities used such technology for first-trimester abortion, and 664 (89.6%) public versus 162 (68.8%) private for second-trimester abortions). Most healthcare facilities (251, 70.7%) had at least one provider trained in PAC. A total of 273 (80.7%) healthcare facilities reported offering contraception to all PAC patients, mainly short-acting methods. Delivery of PAC services depended on the availability of separate evacuation room (public level 2-3: odds ratio [OR] 22.93; public level 4-6: OR 77.14), and the number of family planning methods offered within the facility (public level 2-3: OR 1.38; public level 4-6 OR 1.57; private level 2-3: OR 2.27; private level 4-5: 4.89). CONCLUSION: Effective monitoring of PAC services, particularly among private healthcare facilities, might improve overall quality of services.

Modelling the influence of temperature and rainfall on malaria incidence in four endemic provinces of Zambia using semiparametric Poisson regression.

Although malaria morbidity and mortality are greatly reduced globally owing to great control efforts, the disease remains the main contributor. In Zambia, all provinces are malaria endemic. However, the transmission intensities vary mainly depending on environmental factors as they interact with the vectors. Generally in Africa, possibly due to the varying perspectives and methods used, there is variation on the relative importance of malaria risk determinants. In Zambia, the role climatic factors play on malaria case rates has not been determined in combination of space and time using robust methods in modelling. This is critical considering the reversal in malaria reduction after the year 2010 and the variation by transmission zones. Using a geoadditive or structured additive semiparametric Poisson regression model, we determined the influence of climatic factors on malaria incidence in four endemic provinces of Zambia. We demonstrate a strong positive association between malaria incidence and precipitation as well as minimum temperature. The risk of malaria was 95% lower in Lusaka (ARR=0.05, 95% CI=0.04-0.06) and 68% lower in the Western Province (ARR=0.31, 95% CI=0.25-0.41) compared to Luapula Province. North-western Province did not vary from Luapula Province. The effects of geographical region are clearly demonstrated by the unique behaviour and effects of minimum and maximum temperatures in the four provinces. Environmental factors such as landscape in urbanised places may also be playing a role.

Tobacco use and mass media utilization in sub-Saharan Africa.

BACKGROUND: Media utilization has been identified as an important determinant of tobacco use. We examined the association between self-reported tobacco use and frequency of mass media utilization by women and men in nine low-to middle-income sub-Saharan African countries. METHODOLOGY/PRINCIPAL FINDINGS: Data for the study came from Demographic and Health Surveys conducted in Burkina Faso, Ethiopia, Liberia, Lesotho, Malawi, Swaziland, Uganda, Zambia and Zimbabwe over the period 2006-2011. Each survey population was a cross-sectional sample of women aged 15-49 years and men aged 15-59 years, with information on tobacco use and media access being obtained by face-to-face interviews. An index of media utilization was constructed based on responses to questions on the frequency of reading newspapers, frequency of watching television and frequency of listening to the radio. Demographic and socioeconomic variables were considered as potentially confounding covariates. Logistic regression models with country and cluster specific random effects were estimated for the pooled data. RESULTS: The risk of cigarette smoking increased with greater utilization to mass media. The use of smokeless tobacco and tobacco use in general declined with greater utilization to mass media. The risk of tobacco use was 5% lower in women with high media utilization compared to those with low media utilization [Adjusted Odds Ratio (AOR) = 0.95, 95% confidence interval (CI):0.82-1.00]. Men with a high media utilization were 21% less likely to use tobacco compared to those with low media utilization [AOR = 0.79, 95%CI = 0.73-0.85]. In the male sample, tobacco use also declined with the increased frequency of reading newspapers (or magazines), listening to radio and watching television. CONCLUSIONS: Mass media campaigns, conducted in the context of comprehensive tobacco control programmes, can reduce the prevalence of tobacco smoking in sub-Saharan Africa. The reach, intensity, duration and type of messages are important aspects of the campaigns but need to also address all forms of tobacco use.

Bayesian mapping of HIV infection among women of reproductive age in Rwanda.

HIV prevalence is rising and has been consistently higher among women in Rwanda whereas a decreasing national HIV prevalence rate in the adult population has stabilised since 2005. Factors explaining the increased vulnerability of women to HIV infection are not currently well understood. A statistical mapping at smaller geographic units and the identification of key HIV risk factors are crucial for pragmatic and more efficient interventions. The data used in this study were extracted from the 2010 Rwanda Demographic and Health Survey data for 6952 women. A full Bayesian geo-additive logistic regression model was fitted to data in order to assess the effect of key risk factors and map district-level spatial effects on the risk of HIV infection. The results showed that women who had STIs, concurrent sexual partners in the 12 months prior to the survey, a sex debut at earlier age than 19 years, were living in a woman-headed or high-economic status household were significantly associated with a higher risk of HIV infection. There was a protective effect of high HIV knowledge and perception. Women occupied in agriculture, and those residing in rural areas were also associated with lower risk of being infected. This study provides district-level maps of the variation of HIV infection among women of child-bearing age in Rwanda. The maps highlight areas where women are at a higher risk of infection; the aspect that proximate and distal factors alone could not uncover. There are distinctive geographic patterns, although statistically insignificant, of the risk of HIV infection suggesting potential effectiveness of district specific interventions. The results also suggest that changes in sexual behaviour can yield significant results in controlling HIV infection in Rwanda.