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Objectives The prevalence of all epilepsies (both convulsive and non-convulsive seizures) in Low- and Middle-Income Countries (LMIC), particularly sub-Saharan Africa is unknown. Under estimation of non-convulsive epilepsies in data from these countries may lead to inadequate and sub-optimal allocation of resources to control and prevent epilepsy. We determined the prevalence of all types of epilepsies and compared the mortality between convulsive seizures and non-convulsive seizures in a resource limited rural area in Kenya. Methods Trained clinicians identified cases of epilepsy in a randomly selected sample of 4,441 residents in the Kilifi Health and Demographic Surveillance System site using a cross-sectional survey design. Seizure types were classified by epileptologists using the current guidelines of the International League Against Epilepsy (ILAE). We estimated prevalence for epilepsy with convulsive seizures and non-convulsive seizures and for epilepsy with non-convulsive seizures only and compared premature mortality between these groups of seizures. Results Of the 4441 people visited, 141 had lifetime epilepsy and 96 active epilepsy, which is a crude prevalence of 31.7/1,000 persons (95% CI: 26.6-36.9) and 21.6/1,000 (95% CI: 17.3-25.9), respectively. Both convulsive and non-convulsive seizures occurred in 7% people with epilepsy (PWE), only convulsive seizures in 52% and only non-convulsive seizures in 35% PWE; there was insufficient information to classify epilepsy in the remainder 6%. The age- and sex-adjusted prevalence of lifetime people was 23.5/1,000 (95% CI: 11.0-36.0), with the adjusted prevalence of epilepsy with non-convulsive seizures only estimated at 8.2/1,000 (95%CI:3.9-12.6). The mortality rate in PWE was 6.3/1,000 (95%CI: 3.4-11.8), compared to 2.8/1,000 (2.3-3.3) in those without epilepsy; hazard ratio (HR) =2.31 (1.22-4.39; p=0.011). The annual mortality rate was 11.2/1,000 (95%CI: 5.3-23.4) in PWE with convulsive and non-convulsive seizures and none died in PWE with non-convulsive seizures alone. Conclusions Our study shows that epilepsy with non-convulsive seizures is common and adds to the prevalence of previously reported estimates of active convulsive epilepsy. Both epilepsy with convulsive seizures and that with non-convulsive seizures should be identified for optimising treatment and for planning resource allocation.

Background There is substantial evidence that immunization is one of the most significant and cost-effective pillars of preventive and promotive health interventions. Effective childhood immunization coverage is thus essential in stemming persistent childhood illnesses. The main indicator of performance of the immunisation programme is the third dose of diphtheria-tetanus-pertussis (DTP3) vaccine for children, because it mirrors the completeness of a child’s immunisation schedule. Spatial access to a health facility, especially in SSA countries, is a significant determinant of DTP3 vaccination coverage as the vaccine is mainly administered during routine immunisation schedules at health facilities. Rural areas and densely populated informal settlements are most affected by poor access to healthcare services. We therefore sought to determine vaccination coverage of DTP3, estimate the travel time to health facilities offering immunisation services, and explore of its effect on immunisation coverage in one of the predominantly rural counties in the coast of Kenya.Methods Coordinates of health facilities, information on land cover, digital elevation model, and road network were used to compute spatial accessibility to immunising health facilities for eligible children within Kaloleni-Rabai Community Health Demographic Surveillance System (HDSS). To explore the effect of the travel-time on DTP3 coverage, we fitted a hierarchical multivariable model adjusting for other apriori identified confounding factors. Results Spatial access to health facilities that offer immunization services significantly affected DTP3 coverage with travel times of more than one hour to a health facility significantly associated with reduced odds of receiving DTP3 vaccine (AOR= 0.84 (95% CI 0.74 – 0.94).Conclusion Increased travel time is a significant barrier to the uptake of facility-delivered immunizations in this rural community. To improve immunisation coverage, local health authorities and policy makers in remote settings can use high resolution maps to identify areas where distance and travel time may impede achievement of high immunizations coverage and identify appropriate interventions. These could include improving the road network, establishing new health centres and/or stepping up health outreach activities that include vaccinations in hard to reach areas within the county.

Objective To determine the prevalence of active convulsive epilepsy (ACE) and describe the clinical characteristics and associated factors among a rural Ugandan population. Methods The entire population in Iganga/Mayuge Health Demographic Surveillance Site (IM-HDSS) was screened using two questions about seizures during a door-to-door census exercise. Those who screened positive were assessed by a clinician to confirm diagnosis of epilepsy. A case control study with the patients diagnosed with ACE as the cases and age/sex-matched controls in a ratio of 1:1 was conducted. Results A total of 64,172 (92.8%) IM-HDSS residents, with a median age of 15.0 years (interquartile range [IQR]: 8.0–29.0), were screened for epilepsy. There were 152 confirmed ACE cases, with a prevalence of 10.3/1,000 (95% confidence interval [CI]: 9.5– 11.1) adjusted for nonresponse and screening sensitivity. Prevalence declined with age, with the highest prevalence in the 0–5 years age group. In an analysis of n = 241 that included cases not identified in the survey, nearly 70% were unaware of their diagnosis. Seizures were mostly of focal onset in 193 (80%), with poor electroencephalogram (EEG) agreement with seizure semiology. Antiepileptic drug use was rare, noted in 21.2% (95% CI: 16.5–25.8), and 119 (49.3%) reported using traditional medicines. History of an abnormal antenatal period (adjusted odds ratio [aOR] 10.28; 95%CI 1.26– 83.45; p = 0.029) and difficulties in feeding, crying, breathing in the perinatal period (aOR 10.07; 95%CI 1.24–81.97; p = 0.031) were associated with ACE in children. In adults a family history of epilepsy (aOR 4.38 95%CI 1.77–10.81; p = 0.001) was the only factor associated with ACE. Significance There is a considerable burden of epilepsy, low awareness, and a large treatment gap in this population of rural sub-Saharan Africa. The identification of adverse perinatal events as a risk factor for developing epilepsy in children suggests that epilepsy burden may be decreased by improving obstetric and postnatal care.

Why was the cohort set up?In many resource-constrained settings, availability of reli-able vital statistics and health information is limited bylack of proper system for civil registration and health infor-mation. This is further limited by the fact that the majorityof population health events, such as births, morbidity andmortality, occur outside the reach of these systems. In par-ticular, obtaining credible data from rural and remote ge-ographies can be even more constrained. The developmentof population-based surveillance systems in resource-constrained countries to monitor demographic and healthevents in these countries has as its basis the limited capac-ity of civil registration and health information systems.Locally rooted surveillance systems that are embedded inthe nexus of existing community structures and localhealth systems can serve to address this gap.

Background Acute symptomatic seizures and febrile seizures are common in children admitted to hospitals in Africa and may be markers of brain dysfunction. They may be associated with behavioural and emotional problems, but there are no published community-based studies in Africa. Methods We screened 7047 children aged 1–6 years (randomly sampled from 50,000 in the community) for seizures (using seven questions) and invited those who screened positive and a proportion of negatives for a clinical assessment. Risk factors were identified using a parental questionnaire. Behavioural and emotional problems were examined using the Child Behaviour Checklist (CBCL) in 3273 children randomly selected from 7047. Generalised linear models with appropriate link functions were used to determine risk factors and associations between behavioural or emotional problems and acute seizures. Sobel–Goodman mediation tests were used to investigate if the association between acute seizures and CBCL scores was mediated by co-diagnosis of epilepsy. Results Acute seizures were identified in 429 (6.1%) preschool children: 3.2% (95% confidence interval CI: 2.9–3.5%) for symptomatic seizures, and 2.9% (95% CI: 2.6–3.3%) for febrile seizures. Risk factors for acute seizures included family history of febrile seizures (odds ratio OR = 3.19; 95% CI: 2.03–5.01) and previous hospitalisation (OR = 6.65; 95% CI: 4.60–9.63). Total CBCL problems occurred more frequently in children with acute seizures (27%; 95% CI: 21–34%) than for those without seizures (11%; 95% CI: 11–12%; chi-squared p ≤ 0.001). Acute seizures were associated with total CBCL problems (adjusted risk ratio (aRR) = 1.92; 95% CI: 1.34–2.77), externalising problems (aRR = 1.82; 95% CI: 1.21–2.75) and internalising problems (aRR = 1.57; 95% CI: 1.22–2.02), with the proportion of the comorbidity mediated by a co-diagnosis of epilepsy being small (15.3%; 95% CI: 4.5–34.9%). Risk factors for this comorbidity included family history of febrile seizures (risk ratio (RR) = 3.36; 95% CI: 1.34–8.41), repetitive acute seizures (β = 0.36; 95% CI: 0.15–0.57) and focal acute seizures (RR = 1.80; 95% CI: 1.05–3.08). Conclusions Acute seizures are common in preschool children in this area and are associated with behavioural and emotional problems. Both conditions should be assessed and addressed in children. Electronic supplementary material The online version of this article (10.1186/s12916-018-1021-y) contains supplementary material, which is available to authorized users.

Epilepsy is a common neurologic disorder directly affecting about 70 million people in the world, with about 90% residing in lower‐and middle‐income countries.1 The treatment gap for epilepsy is large (up to 90%) in these areas, and this is in part due to negative attitudes toward biomedical services, cost of accessing diagnosis and treatment, and traditional beliefs about the cause of epilepsy.2, 3 People with epilepsy (PWE) are thought to have more hospital admissions than those with other chronic neurologic disorders,4 and is the third most common after stroke and spinal cord injuries in sub‐Saharan Africa (SSA).5 Epilepsy‐related hospital admissions are increasing in high‐income countries; for example, the rate of hospital use increased from 66 to 68/100,000 persons/year over 10 years in England and Wales,4 and by 27% over 12 years in the United States.6 In the American study, epilepsy accounted for more than half of all hospital stays among admissions of PWE, with respiratory‐related complications being the most common causes for admission.6 The hospital admission rates would be expected to be higher in SSA compared to the West because of the higher prevalence of epilepsy7 and the larger treatment gap.3 In addition, epilepsy in Africa is associated with increased complications such as status epilepticus, burns, and head injuries,8 which often require treatment at the hospital. Nevertheless, there are few published studies that document the burden, causes, and duration of hospitalization in PWE in SSA, where epilepsy may add a considerable burden on the health system. In Zambia PWE had a poorer socioeconomic status compared to their peers with other medical conditions,9 but the focus of this study was not to examine the burden of hospitalization due to epilepsy. This study estimates the incidence of admissions with epilepsy, the associated disability‐adjusted life years (DALYs) and determines the important causes and risk factors of admission to a rural hospital among PWE. We further examined the risk factors associated with the major outcomes (duration of hospitalization and mortality) among PWE.

Background In Africa, where access to specialist medical services is often limited, telemedicine, the use of information and communication technologies for the provision of healthcare at a distance, can contribute towards enhancing access to healthcare. Informed consent is considered the cornerstone of ethical practice, especially when technology and techniques are considered new and or unproven. It is advised that informed consent should be gained in the patient’s mother tongue. However, many African languages have not kept pace with technology and lack the words and terms needed to describe computing and technical terms. Additionally, even when present, patients may not understand these words and terms. This affects the validity of informed consent given. Methods Forty relevant computer terms and words used when explaining telemedicine during the consent process were selected and translated into Kiswahili. Patients at the outpatient department of the Kilifi County Hospital in Kenya participated. The study consisted of two phases. In the first, 50 people were asked whether they understood the translated words and terms and were able to explain their meaning. In the second (n = 42) they were asked to explain the meaning of the translated word, the original English word, and those words that could not be translated. Results Of the 40 terms, 14 could not be translated (35%). A total of 92 people attending the Kilifi County Hospital participated. Their average age was 31.2 ± 10.6 y, 70.7% were female and 55.4% were from rural areas. More than half of the respondents did not understand videoconference, store and forward, digital photograph, wireless, World Wide Web, antivirus or email in either language. No-one understood the words telemedicine, firewall, encryption, decryption and tele-diagnosis. Conclusions Currently it is unlikely that valid informed consent can be obtained for a telemedicine encounter in Kiswahili. Innovative solutions are required to overcome the barrier of languages failing to keep pace with technology and their effect on consent.

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 centre's 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

Summary Background Many people with epilepsy in low-income countries do not receive appropriate biomedical treatment. This epilepsy treatment gap might be caused by patients not seeking biomedical treatment or not adhering to prescribed antiepileptic drugs (AEDs). We measured the prevalence of and investigated risk factors for the epilepsy treatment gap in rural Kenya. Methods All people with active convulsive epilepsy identified during a cross-sectional survey of 232 176 people in Kilifi were approached. The epilepsy treatment gap was defined as the percentage of people with active epilepsy who had not accessed biomedical services or who were not on treatment or were on inadequate treatment. Information about risk factors was obtained through a questionnaire-based interview of sociodemographic characteristics, socioeconomic status, access to health facilities, seizures, stigma, and beliefs and attitudes about epilepsy. The factors associated with people not seeking biomedical treatment and not adhering to AEDs were investigated separately, adjusted for age. Findings 673 people with epilepsy were interviewed, of whom 499 (74%) reported seeking treatment from a health facility. Blood samples were taken from 502 (75%) people, of whom 132 (26%) reported taking AEDs, but 189 (38%) had AEDs detectable in the blood. The sensitivity and specificity of self-reported adherence compared with AEDs detected in blood were 38·1% (95% CI 31·1–45·4) and 80·8% (76·0–85·0). The epilepsy treatment gap was 62·4% (58·1–66·6). In multivariable analysis, failure to seek biomedical treatment was associated with a patient holding traditional animistic religious beliefs (adjusted odds ratio 1·85, 95% CI 1·11–2·71), reporting negative attitudes about biomedical treatment (0·86, 0·78–0·95), living more than 30 km from health facilities (3·89, 1·77–8·51), paying for AEDs (2·99, 1·82–4·92), having learning difficulties (2·30, 1·29–4·11), having had epilepsy for longer than 10 years (4·60, 2·07–10·23), and having focal seizures (2·28, 1·50–3·47). Reduced adherence was associated with negative attitudes about epilepsy (1·10, 1·03–1·18) and taking of AEDs for longer than 5 years (3·78, 1·79–7·98). Interpretation The sensitivity and specificity of self-reported adherence is poor, but on the basis of AED detection in blood almost two-thirds of patients with epilepsy were not on treatment. Education about epilepsy and making AEDs freely available in health facilities near people with epilepsy should be investigated as potential ways to reduce the epilepsy treatment gap. Funding Wellcome Trust.

We estimated premature mortality and identified causes of death and associated factors in people with active convulsive epilepsy (ACE) in rural Kenya.In this prospective population-based study, people with ACE were identified in a cross-sectional survey and followed up regularly for 3 years, during which information on deaths and associated factors was collected. We used a validated verbal autopsy tool to establish putative causes of death. Age-specific rate ratios and standardized mortality ratios were estimated. Poisson regression was used to identify mortality risk factors.There were 61 deaths among 754 people with ACE, yielding a rate of 33.3/1,000 persons/year. Overall standardized mortality ratio was 6.5. Mortality was higher across all ACE age groups. Nonadherence to antiepileptic drugs (adjusted rate ratio [aRR] 3.37), cognitive impairment (aRR 4.55), and age (50+ years) (rate ratio 4.56) were risk factors for premature mortality. Most deaths (56%) were directly related to epilepsy, with prolonged seizures/possible status epilepticus (38%) most frequently associated with death; some of these may have been due to sudden unexpected death in epilepsy (SUDEP). Possible SUDEP was the likely cause in another 7%.Mortality in people with ACE was more than 6-fold greater than expected. This may be reduced by improving treatment adherence and prompt management of prolonged seizures and supporting those with cognitive impairment.

Objectives The epilepsy treatment gap is largest in resource-poor countries. We evaluated the efficacy of a 1-day health education program in a rural area of Kenya. The primary outcome was adherence to antiepileptic drugs (AEDs) as measured by drug levels in the blood, and the secondary outcomes were seizure frequency and Kilifi Epilepsy Beliefs and Attitudes Scores (KEBAS). Methods Seven hundred thirty-eight people with epilepsy (PWE) and their designated supporter were randomized to either the intervention (education) or nonintervention group. Data were collected at baseline and 1 year after the education intervention was administered to the intervention group. There were 581 PWE assessed at both time points. At the end of the study, 105 PWE from the intervention group and 86 from the nonintervention group gave blood samples, which were assayed for the most commonly used AEDs (phenobarbital, phenytoin, and carbamazepine). The proportions of PWE with detectable AED levels were determined using a standard blood assay method. The laboratory technicians conducting the assays were blinded to the randomization. Secondary outcomes were evaluated using questionnaires administered by trained field staff. Modified Poisson regression was used to investigate the factors associated with improved adherence (transition from nonoptimal AED level in blood at baseline to optimal levels at follow-up), reduced seizures, and improved KEBAS, which was done as a post hoc analysis. This trial is registered in ISRCTN register under ISRCTN35680481. Results There was no significant difference in adherence to AEDs based on detectable drug levels (odds ratio [OR] 1.46, 95% confidence interval [95% CI] 0.74–2.90, p = 0.28) or by self-reports (OR 1.00, 95% CI 0.71–1.40, p = 1.00) between the intervention and nonintervention group. The intervention group had significantly fewer beliefs about traditional causes of epilepsy, cultural treatment, and negative stereotypes than the nonintervention group. There was no difference in seizure frequency. A comparison of the baseline and follow-up data showed a significant increase in adherence—intervention group (36–81% [p < 0.001]) and nonintervention group (38–74% [p < 0.001])—using detectable blood levels. The number of patients with less frequent seizures (≤3 seizures in the last 3 months) increased in the intervention group (62–80% [p = 0.002]) and in the nonintervention group (67–75% [p = 0.04]). Improved therapeutic adherence (observed in both groups combined) was positively associated with positive change in beliefs about risks of epilepsy (relative risk [RR] 2.00, 95% CI 1.03–3.95) and having nontraditional religious beliefs (RR 2.01, 95% CI 1.01–3.99). Reduced seizure frequency was associated with improved adherence (RR 1.72, 95% CI 1.19–2.47). Positive changes in KEBAS were associated with having tertiary education as compared to none (RR 1.09, 95% CI 1.05–1.14). Significance Health education improves knowledge about epilepsy, but once only contact does not improve adherence. However, sustained education may improve adherence in future studies.