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High-quality vaccine-preventable disease (VPD) surveillance data are critical for timely outbreak detection and response. In 2019, the World Health Organization (WHO) African Regional Office (AFRO) began transitioning from Epi Info, a free, CDC-developed statistical software package with limited capability to integrate with other information systems, affecting reporting timeliness and data use, to District Health Information Software 2 (DHIS2). DHIS2 is a free and open-source software platform for electronic aggregate Integrated Disease Surveillance and Response (IDSR) and case-based surveillance reporting. A national-level reporting system, which provided countries with the option to adopt this new system, was introduced. Regionally, the Epi Info database will be replaced with a DHIS2 regional data platform. This report describes the phased implementation from 2019 to the present. Phase one (2019-2021) involved developing IDSR aggregate and case-based surveillance packages, including pilots in the countries of Mali, Rwanda, and Togo. Phase two (2022) expanded national-level implementation to 27 countries and established the WHO AFRO DHIS2 regional data platform. Phase three (from 2023 to the present) activities have been building local capacity and support for country reporting to the regional platform. By February 2024, eight of 47 AFRO countries had adopted both the aggregate IDSR and case-based surveillance packages, and two had successfully transferred VPD surveillance data to the AFRO regional platform. Challenges included limited human and financial resources, the need to establish data-sharing and governance agreements, technical support for data transfer, and building local capacity to report to the regional platform. Despite these challenges, the transition to DHIS2 will support efficient data transmission to strengthen VPD detection, response, and public health emergencies through improved system integration and interoperability., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. No potential conflicts of interest were disclosed.

Background: Malawi has one of the highest under-five mortality rates in Sub Sahara Africa. Understanding the factors that contribute to child mortality in Malawi is crucial for the development and implementation of effective interventions to reduce child mortality. The aim of this study is to use survival analysis in modeling time to death for under-five children in Malawi. In turn, identify potential risk factors for child mortality and inform the development of interventions to reduce child mortality in the country., Method: This study used data from all births that occurred in the five years leading up to the 2015/16 Malawi Demographic and Health Survey. The Frailty hazard model was applied to predict infant survival in Malawi. In this analysis, the outcome of interest was death and it had two possible outcomes: "dead" or "alive". Age at death was regarded as the survival time variable. Infants who were still alive at the time of the study as of the day of the interview were considered as censored observations in the analysis., Results: A total of 17,286 live births born during the 5 years preceding the survey were analysed. The study found that the risk of death was higher among children born to mothers aged 30-39 and 40 or older compared to teen mothers. Infants whose mothers attended fewer than four antenatal care visits were also found to be at a higher risk of death. On the other hand, the study found that using mosquito nets and early breastfeeding were associated with a lower risk of death, as were being male and coming from a wealthier household., Conclusion: The study reveals a notable decline in infant mortality rates as under-five children age, underscoring the challenge of ensuring newborn survival. Factors such as maternal age, birth order, socioeconomic status, mosquito net usage, early breastfeeding initiation, geographic location, and child's sex are key predictors of under-five mortality. To address this, public health strategies should prioritize interventions targeting these predictors to reduce under-five mortality rates., (© 2024. The Author(s).)

Background: In preventive drug trials such as intermittent preventive treatment for malaria prevention during pregnancy (IPTp), where there is repeated treatment administration, recurrence of adverse events (AEs) is expected. Challenges in modelling the risk of the AEs include accounting for time-to-AE and within-patient-correlation, beyond the conventional methods. The correlation comes from two sources; (a) individual patient unobserved heterogeneity (i.e. frailty) and (b) the dependence between AEs characterised by time-dependent treatment effects. Potential AE-dependence can be modelled via time-dependent treatment effects, event-specific baseline and event-specific random effect, while heterogeneity can be modelled via subject-specific random effect. Methods that can improve the estimation of both the unobserved heterogeneity and treatment effects can be useful in understanding the evolution of risk of AEs, especially in preventive trials where time-dependent treatment effect is expected., Methods: Using both a simulation study and the Chloroquine for Malaria in Pregnancy (NCT01443130) trial data to demonstrate the application of the models, we investigated whether the lognormal shared frailty models with restricted cubic splines and non-proportional hazards (LSF-NPH) assumption can improve estimates for both frailty variance and treatment effect compared to the conventional inverse Gaussian shared frailty model with proportional hazard (ISF-PH), in the presence of time-dependent treatment effects and unobserved patient heterogeneity. We assessed the bias, precision gain and coverage probability of 95% confidence interval of the frailty variance estimates for the models under varying known unobserved heterogeneity, sample sizes and time-dependent effects., Results: The ISF-PH model provided a better coverage probability of 95% confidence interval, less bias and less precise frailty variance estimates compared to the LSF-NPH models. The LSF-NPH models yielded unbiased hazard ratio estimates at the expense of imprecision and high mean square error compared to the ISF-PH model., Conclusion: The choice of the shared frailty model for the recurrent AEs analysis should be driven by the study objective. Using the LSF-NPH models is appropriate if unbiased hazard ratio estimation is of primary interest in the presence of time-dependent treatment effects. However, ISF-PH model is appropriate if unbiased frailty variance estimation is of primary interest., Trial Registration: ClinicalTrials.gov; NCT01443130., (© 2022. The Author(s).)

Background: In drug trials, adverse events (AEs) burden can induce treatment non-adherence or discontinuation. The non-adherence and discontinuation induce selection bias, affecting drug safety interpretation. Nested case-control (NCC) study can efficiently quantify the impact of the AEs, although choice of sampling approach is challenging. We investigated whether NCC study with incidence density sampling is more efficient than NCC with path sampling under conditional logistic or weighted Cox models in assessing the effect of AEs on treatment non-adherence and participation in preventive antimalarial drug during pregnancy trial., Methods: Using data from a trial of medication to prevent malaria in pregnancy that randomized 600 women to receive chloroquine or sulfadoxine-pyrimethamine during pregnancy, we conducted a NCC study assessing the role of prospectively collected AEs, as exposure of interest, on treatment non-adherence and study non-completion. We compared estimates from NCC study with incidence density against those from NCC with path sampling under conditional logistic and weighted Cox models., Results: Out of 599 women with the outcomes of interest, 474 (79%) experienced at least one AE before delivery. For conditional logistic model, the hazard ratio for the effect of AE occurrence on treatment non-adherence was 0.70 (95% CI: 0.42, 1.17; p = 0.175) under incidence density sampling and 0.68 (95% CI: 0.41, 1.13; p = 0.137) for path sampling. For study non-completion, the hazard ratio was 1.02 (95% CI: 0.56, 1.83; p = 0.955) under incidence density sampling and 0.85 (95% CI: 0.45, 1.60; p = 0.619) under path sampling. We obtained similar hazard ratios and standard errors under incidence density sampling and path sampling whether weighted Cox or conditional logistic models were used., Conclusion: NCC with incidence density sampling and NCC with path sampling are practically similar in efficiency whether conditional logistic or weighted Cox analytical methods although path sampling uses more unique controls to achieve the similar estimates., Trial Registration: ClinicalTrials.gov: NCT01443130., Competing Interests: The authors have declared that no competing interests exist.

Background: In drug trials, clinical adverse events (AEs), concomitant medication and laboratory safety outcomes are repeatedly collected to support drug safety evidence. Despite the potential correlation of these outcomes, they are typically analysed separately, potentially leading to misinformation and inefficient estimates due to partial assessment of safety data. Using joint modelling, we investigated whether clinical AEs vary by treatment and how laboratory outcomes (alanine amino-transferase, total bilirubin) and concomitant medication are associated with clinical AEs over time following artemisinin-based antimalarial therapy., Methods: We used data from a trial of artemisinin-based treatments for malaria during pregnancy that randomized 870 women to receive artemether-lumefantrine (AL), amodiaquine-artesunate (ASAQ) and dihydroartemisinin-piperaquine (DHAPQ). We fitted a joint model containing four sub-models from four outcomes: longitudinal sub-model for alanine aminotransferase, longitudinal sub-model for total bilirubin, Poisson sub-model for concomitant medication and Poisson sub-model for clinical AEs. Since the clinical AEs was our primary outcome, the longitudinal sub-models and concomitant medication sub-model were linked to the clinical AEs sub-model via current value and random effects association structures respectively. We fitted a conventional Poisson model for clinical AEs to assess if the effect of treatment on clinical AEs (i.e. incidence rate ratio (IRR)) estimates differed between the conventional Poisson and the joint models, where AL was reference treatment., Results: Out of the 870 women, 564 (65%) experienced at least one AE. Using joint model, AEs were associated with the concomitant medication (log IRR 1.7487; 95% CI: 1.5471, 1.9503; p < 0.001) but not the total bilirubin (log IRR: -0.0288; 95% CI: - 0.5045, 0.4469; p = 0.906) and alanine aminotransferase (log IRR: 0.1153; 95% CI: - 0.0889, 0.3194; p = 0.269). The Poisson model underestimated the effects of treatment on AE incidence such that log IRR for ASAQ was 0.2118 (95% CI: 0.0082, 0.4154; p = 0.041) for joint model compared to 0.1838 (95% CI: 0.0574, 0.3102; p = 0.004) for Poisson model., Conclusion: We demonstrated that although the AEs did not vary across the treatments, the joint model yielded efficient AE incidence estimates compared to the Poisson model. The joint model showed a positive relationship between the AEs and concomitant medication but not with laboratory outcomes., Trial Registration: ClinicalTrials.gov: NCT00852423., (© 2021. The Author(s).)

The increase in health research in sub-Saharan Africa (SSA) has led to a high demand for biostatisticians to develop study designs, contribute and apply statistical methods in data analyses. Initiatives exist to address the dearth in statistical capacity and lack of local biostatisticians in SSA health projects. The Sub-Saharan African Consortium for Advanced Biostatistics (SSACAB) led by African institutions was initiated to improve biostatistical capacity according to the needs identified by African institutions, through collaborative masters and doctoral training in biostatistics. SACCAB has created a critical mass of biostatisticians and a network of institutions over the last five years and has strengthened biostatistics resources and capacity for health research studies in SSA.  SSACAB comprises 11 universities and four research institutions which are supported by four European universities.  In 2015, only four universities had established Masters programmes in biostatistics and SSACAB supported the remaining seven to develop Masters programmes. In 2019 the University of the Witwatersrand became the first African institution to gain Royal Statistical Society accreditation for a Biostatistics Masters programme. A total of 150 fellows have been awarded scholarships to date of which 123 are Masters fellowships (41 female) of whom 58 have already graduated. Graduates have been employed in African academic (19) and research (15) institutions and 10 have enrolled for PhD studies. A total of 27 (10 female) PhD fellowships have been awarded; 4 of them are due to graduate by 2020. To date, SSACAB Masters and PhD students have published 17 and 31 peer-reviewed articles, respectively. SSACAB has also facilitated well-attended conferences, face-to-face and online short courses. Pooling of limited biostatistics resources in SSA combined with co-funding from external partners has shown to be an effective strategy for the development and teaching of advanced biostatistics methods, supervision and mentoring of PhD candidates., Competing Interests: No competing interests were disclosed., (Copyright: © 2020 Chirwa TF et al.)

Background: Drug safety assessments in clinical trials present unique analytical challenges. Some of these include adjusting for individual follow-up time, repeated measurements of multiple outcomes and missing data among others. Furthermore, pre-specifying appropriate analysis becomes difficult as some safety endpoints are unexpected. Although existing guidelines such as CONSORT encourage thorough reporting of adverse events (AEs) in clinical trials, they provide limited details for safety data analysis. The limited guidelines may influence suboptimal analysis by failing to account for some analysis challenges above. A typical example where such challenges exist are trials of anti-malarial drugs for malaria prevention during pregnancy. Lack of proper standardized evaluation of the safety of antimalarial drugs has limited the ability to draw conclusions about safety. Therefore, a systematic review was conducted to establish the current practice in statistical analysis for preventive antimalarial drug safety in pregnancy., Methods: The search included five databases (PubMed, Embase, Scopus, Malaria in Pregnancy Library and Cochrane Central Register of Controlled Trials) to identify original English articles reporting Phase III randomized controlled trials (RCTs) on anti-malarial drugs for malaria prevention in pregnancy published from January 2010 to July 2019., Results: Eighteen trials were included in this review that collected multiple longitudinal safety outcomes including AEs. Statistical analysis and reporting of the safety outcomes in all the trials used descriptive statistics; proportions/counts (n = 18, 100%) and mean/median (n = 2, 11.1%). Results presentation included tabular (n = 16, 88.9%) and text description (n = 2, 11.1%). Univariate inferential methods were reported in most trials (n = 16, 88.9%); including Chi square/Fisher's exact test (n = 12, 66.7%), t test (n = 2, 11.1%) and Mann-Whitney/Wilcoxon test (n = 1, 5.6%). Multivariable methods, including Poisson and negative binomial were reported in few trials (n = 3, 16.7%). Assessment of a potential link between missing efficacy data and safety outcomes was not reported in any of the trials that reported efficacy missing data (n = 7, 38.9%)., Conclusion: The review demonstrated that statistical analysis of safety data in anti-malarial drugs for malarial chemoprevention in pregnancy RCTs is inadequate. The analyses insufficiently account for multiple safety outcomes potential dependence, follow-up time and informative missing data which can compromise anti-malarial drug safety evidence development, based on the available data.

In Malawi, the current approach to family planning using contraceptive methods is individualised, yet studies have shown that variability in contraceptive-use still remains after accounting for it at individual and household levels. Therefore, this study assessed variability at higher levels such as enumeration areas, districts and regions. Biasness of the estimates was addressed by the use of Bayesian approach. The study used 2015-16 Malawi Demographic Health Survey women data. After ascertaining the significance of association of all explanatory variables with contraceptive use, the top-down (backward) stepwise model selection method was followed in the Bayesian framework using Markov Chain Monte Carlo and defuse priors. Models were compared on the basis of Deviance Information Criteria and significance of parameter estimates was checked via credible intervals while that of cross-cluster variances was checked by examining their diagnostic plots. All the selected socio-demographic factors were strongly associated with contraceptive-use ( p -value <  0.001). These factors include; region, place-of-residence, age, parity, education, occupation, marital-status and religion. It was also found that about 15 and 2.3% of the variation in contraceptive-use was attributed to enumeration area and district clustering, respectively. The single-level model underestimated the parameter estimates by at least 4% for both models. And parity-enumeration area, age-enumeration area and age-district random effects were significant in their respective models. It was also noted that most young women aged between 15 and 24 years were not using any contraceptive methods. The study indicated that there exist significant enumeration area and district heterogeneity on contraceptive use in Malawian women and that random-effect models are the most appropriate models other than single-level models. Thus family planning programs focusing on contraceptive-use should switch to inclusive approach and statistical analyses should consider including enumeration area and district heterogeneity while controlling for the above significant factors. Stakeholders may also consider encouraging young women to use contraceptive methods, if Malawi is to minimize problems due to overpopulation., Competing Interests: Competing interestsThe authors declare that they have no competing interests.

This paper examined care-seeking behaviour and its associated risk factors when a family member had diarrhoea. Data was obtained from a survey conducted in Chikwawa, a district in Southern Malawi. Chikwawa is faced with a number of environmental and socioeconomic problems and currently diarrhoea morbidity in the district is estimated at 24.4%, statistically higher than the national average of 17%. Using hierarchically built data from a survey of 1403 households nested within 33 communities, a series of two level binary logistic regression models with Bayesian estimation were used to determine predictors of care-seeking behaviour. The results show that 68% of mothers used oral rehydration solutions (ORS) the last time a child in their family had diarrhoea. However, when asked on the action they take when a member of their household has diarrhoea two thirds of the mothers said they visit a health facility. Most respondents (73%) mentioned distance and transport costs as the main obstacles to accessing their nearest health facility and the same proportion of respondents mentioned prolonged waiting time and absence of health workers as the main obstacles encountered at the health facilities. The main predictor variables when a member of the family had diarrhoea were maternal age, distance to the nearest health facility, school level, and relative wealth, household diarrhoea endemicity, and household size while the main predictor variables when a child had diarrhoea were existence of a village health committee (VHC), distance to the nearest health facility, and maternal age. Most households use ORS for the treatment of diarrhoea and village health committees and health surveillance assistants (HSAs) are important factors in this choice of treatment. Health education messages on the use and efficacy of ORS to ensure proper and prescribed handling are important. There is need for a comprehensive concept addressing several dimensions of management and proper coordination of delivery of resources and services; availability of adequate healthcare workers at all levels; affordability to accessibility of healthcare resources and services to all communities; acceptability and quality of care; intensification of health education messages on the use and management of ORS, and prompt and timely treatment of diarrhoeal illness., Competing Interests: The authors declare no conflict of interest.

Background: Annual global estimates of perinatal mortality show Malawi among sub-Saharan Africa with the highest rates. Targeted interventions are required to reduce this mortality. This study aimed to quantify small-scale geographical variations in perinatal mortality, and estimate risk factors associated with perinatal mortality in Mchinji district., Methods: As part of the 2005-2010 randomised controlled trial conducted in Mchinji district, prospective data from the control arm of the trial was collected on perinatal mortality. A Structured Additive Regression model was applied to account for influence of both individual and contextual factors, and jointly accounting for nonlinear effects of continuous covariates, spatially structured variation, unstructured heterogeneity and fixed effects. Modelling and inference used a fully Bayesian approach., Results: Factors associated with reduced perinatal mortality were: previous pregnancy; early and consistent use of antenatal care; syphilis test; abdominal examination; pregnancy danger signs advice; skilled birth attendant; normal labour duration; gestation period of at least 9 months; and normal delivery. Perinatals whose mothers had blood test were associated with high probability of dying. Perinatals from mothers between 16 and 40 years had reduced prevalence of dying while those aged less than 16 years and greater than 40 years were associated with higher prevalence of dying. After accounting for all significant covariates, high perinatal mortality was observed in eastern part of the district whereas low perinatal mortality was observed in the western part., Conclusion: Targeting health interventions to higher risk areas and ensuring universal coverage are promising approaches for promoting equity and reducing perinatal mortality., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Developing countries face a huge burden of infectious diseases, a number of which co-exist. This paper estimates the pattern and variation of malaria and diarrhea coexistence in Chikhwawa, a district in Southern Malawi using bivariate multilevel modelling with Bayesian estimation. A probit link was employed to examine hierarchically built data from a survey of individuals (n = 6,727) nested within households (n = 1,380) nested within communities (n = 33). Results show significant malaria [σ²μ₁=0.901 (95% CI:0.746,1.056)] and diarrhea [σ²μ₂=1.009 (95% CI:0.860,1.158)] variations with a strong correlation between them [r(¹,²)μ=0.565] at household level. There are significant malaria [σ²ν₁=0.053 (95% CI: 0.018,0.088)] and diarrhea [σ²ν₂=0.099(95% CI : 0.030,0.168) ] variations at community level but with a small correlation [r(¹,²) ν=0.124] between them. There is also significant correlation between malaria and diarrhea at individual level [ r(¹,²) e=0.241]. These results suggest a close association between reported malaria-like illness and diarrheal illness especially at household and individual levels in Southern Malawi.

Background: After years of implementing Roll Back Malaria (RBM) interventions, the changing landscape of malaria in terms of risk factors and spatial pattern has not been fully investigated. This paper uses the 2010 malaria indicator survey data to investigate if known malaria risk factors remain relevant after many years of interventions., Methods: We adopted a structured additive logistic regression model that allowed for spatial correlation, to more realistically estimate malaria risk factors. Our model included child and household level covariates, as well as climatic and environmental factors. Continuous variables were modelled by assuming second order random walk priors, while spatial correlation was specified as a Markov random field prior, with fixed effects assigned diffuse priors. Inference was fully Bayesian resulting in an under five malaria risk map for Malawi., Results: Malaria risk increased with increasing age of the child. With respect to socio-economic factors, the greater the household wealth, the lower the malaria prevalence. A general decline in malaria risk was observed as altitude increased. Minimum temperatures and average total rainfall in the three months preceding the survey did not show a strong association with disease risk., Conclusions: The structured additive regression model offered a flexible extension to standard regression models by enabling simultaneous modelling of possible nonlinear effects of continuous covariates, spatial correlation and heterogeneity, while estimating usual fixed effects of categorical and continuous observed variables. Our results confirmed that malaria epidemiology is a complex interaction of biotic and abiotic factors, both at the individual, household and community level and that risk factors are still relevant many years after extensive implementation of RBM activities.

Young people in urban slums adopt HIV risk behaviors influenced by their neighborhood factors. Three critical factors in urban slums of Southern and Eastern Africa--the region most affected by the HIV epidemic in the world--are unmet needs of housing, food, and health care, which are associated with HIV sexual risks. Yet, there has been limited attention on how the combination of unmet needs of housing, food, and health care--i.e., material deprivation-relates to sexual risk behavior among young people in urban slums. Cross-sectional data were extracted from the LoveLife survey in South African four provinces--KwaZulu Natal, Mpumalanga, Eastern Cape, and Gauteng, to examine the association between material deprivation and sexual risk behavior among young people aged 18-23 years (263 males, 267 females) in urban slums. Adjusted logistic regression models showed that material deprivation was significantly associated with increased odds of high sexual risk taking for young men (adjusted OR = 1.20; 95 % CI = 1.10, 5.58) and young women (adjusted OR = 1.43; 95 % CI = 1.35, 3.28). Financial difficulty--a proxy for other deprivations--was the most salient influence on young women's high sexual risk taking (adjusted OR = 2.11; 95 % CI = 1.66, 2.70). Localized behavioral HIV prevention interventions should target young people in deprived households.

Substantial development assistance has been directed towards reducing the high malaria burden in Malawi over the past decade. We assessed changes in transmission over this period of malaria control scale-up by compiling community Plasmodium falciparum rate (PfPR) data during 2000-2011 and used model-based geostatistical methods to predict mean PfPR2-10 in 2000, 2005, and 2010. In addition, we calculated population-adjusted prevalences and populations at risk by district to inform malaria control program priority setting. The national population-adjusted PfPR2-10 was 37% in 2010, and we found no evidence of change over this period of scale-up. The entire population of Malawi is under meso-endemic transmission risk, with those in districts along the shore of Lake Malawi and Shire River Valley under highest risk. The lack of change in prevalence confirms modeling predictions that when compared with lower transmission, prevalence reductions in high transmission settings require greater investment and longer time scales.

Miguel Sanjoaquin and colleagues describe their experience of setting up an electronic patient records system in a large referral hospital in Blantyre, Malawi.

Objectives: To estimate and quantify childhood mortality, its spatial correlates and the impact of potential correlates using recent census data from three sub-Saharan African countries (Rwanda, Senegal and Uganda), where evidence is lacking., Design: Cross-sectional., Setting: Nation-wide census samples from three African countries participating in the 2010 African Census round. All three countries have conducted recent censuses and have information on mortality of children under 5 years., Participants: 111 288 children under the age of 5 years in three countries., Primary and Secondary Outcome Measures: Under-five mortality was assessed alongside potential correlates including geographical location (where children live), and environmental, bio-demographic and socioeconomic variables., Results: Multivariate analysis indicates that in all three countries the overall risk of child death in the first 5 years of life has decreased in recent years (Rwanda: HR=0.04, 95% CI 0.02 to 0.09; Senegal: HR=0.02 (95% CI 0.02 to 0.05); Uganda: HR=0.011 (95% CI 0.006 to 0.018). In Rwanda, lower deaths were associated with living in urban areas (0.79, 0.73, 0.83), children with living mother (HR=0.16, 95% CI 0.15 to 0.17) or living father (HR=0.38, 95% CI 0.36 to 0.39). Higher death was associated with male children (HR=1.06, 95% CI 1.02 to 1.08) and Christian children (HR=1.14, 95% CI 1.05 to 1.27). Children less than 1 year were associated with higher risk of death compared to older children in the three countries. Also, there were significant spatial variations showing inequalities in children mortality by geographic location. In Uganda, for example, areas of high risk are in the south-west and north-west and Kampala district showed a significantly reduced risk., Conclusions: We provide clear evidence of considerable geographical variation of under-five mortality which is unexplained by factors considered in the data. The resulting under-five mortality maps can be used as a practical tool for monitoring progress within countries for the Millennium Development Goal 4 to reduce under-five mortality in half by 2015.

A survey was conducted in Southern Malawi to examine the pattern of mothers' knowledge on diarrhoea. Diarrhoea morbidity in the district is estimated at 24.4%, statistically higher than the national average at 17%. Using hierarchically built data from a survey, a multilevel threshold of change analysis was used to determine predictors of knowledge about diarrhoeal aetiology, clinical features, and prevention. The results show a strong hierarchical structured pattern in overall maternal knowledge revealing differences between communities. Responsible mothers with primary or secondary school education were more likely to give more correct answers on diarrhoea knowledge than those without any formal education. Responsible mothers from communities without a health surveillance assistant were less likely to give more correct answers. The results show that differences in diarrhoeal knowledge do exist between communities and demonstrate that basic formal education is important in responsible mother's understanding of diseases. The results also reveal the positive impact health surveillance assistants have in rural communities.

A cross sectional study was conducted to estimate the prevalence and correlates of suicidal ideation among in-school adolescents in Zambia. Backward logistic regression analysis was conducted to assess the association between relevant predictor variables and suicidal ideation within the last 12 months. A total of 1970 in-school adolescents who participated in the Zambia Global School-Based Health Survey in 2004 responded to the question on suicidal ideation. Overall, 54.0% were males, 40.8% were current drinkers, and 35.9% ever smoked marijuana (cannabis). Altogether 31.3% reported suicidal ideation in the past 12 months (males = 31.1%; females = 31.4%). Being male (OR = 1.05; 95%CI 1.03, 1.05): being <14 years old (OR = 1.21; 95%CI 1.19, 1.23), having been drunk (OR = 1.28; 95%CI 1.27, 1.29). worried (OR= 1.05; 95%CI 1.04, 1.06), sad or hopeless in the past 12 months (OR = 1.02; 95%CI 1.01, 1.03) and ever used marijuana (OR = 1.18; 95%CI 1.17, 1.19) were positively associated with suicidal ideation. Loneliness appeared to be protective (OR = 0.92; 95%CI 0.91, 0.92). All the results, except for ever smoked marijuana and ever been drunk, may have been biased due to non-response to the question on suicidal ideation. A series of cross sectional studies should be conducted to monitor changes in behavioural factors among others ever smoked marijuana and ever been drunk in order to broaden our understanding of factors that may be causing adolescents to seriously consider committing suicide.