Anthony K. Ngugi

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

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

The epilepsy treatment gap in developing countries : A systematic review of the magnitude, causes, and intervention strategies

In many developing countries, people with epilepsy do not receive appropriate treatment for their condition, a phenomenon called the treatment gap (TG). We carried out a systematic review to investigate the magnitude, causes, and intervention strategies to improve outcomes in developing countries. We systematically searched MEDLINE, EMBASE, and PsycINFO databases, supplemented by a hand search of references in the key papers. The degree of heterogeneity and a pooled TG estimate were determined using metaanalysis techniques. The estimates were further stratified by continent and location of study (urban, rural). Twenty‐seven studies met the inclusion criteria: twelve from Africa, nine from Asia and six from Latin America. We observed a high degree of heterogeneity and inconsistency between studies. The overall estimate of the TG was 56/100 [95% confidence interval (CI) 31.1–100.0]. The variation in estimates could possibly be explained by nonuniform TG estimation methods and the diverse study populations, among other factors. The TG was mainly attributed to inadequate skilled manpower, cost of treatment, cultural beliefs, and unavailability of antiepileptic drugs (AEDs). These factors have been addressed using different intervention strategies, such as education and supply of AEDs. Future research should estimate the TG coherently and develop sustainable interventions that will address the causes.

Incidence of epilepsy A systematic review and meta-analysis

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

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

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

Risk factors associated with the epilepsy treatment gap in Kilifi, Kenya: a cross-sectional study

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.

Exposure to Multiple Parasites Is Associated with the Prevalence of Active Convulsive Epilepsy in Sub-Saharan Africa

Background Epilepsy is common in developing countries, and it is often associated with parasitic infections. We investigated the relationship between exposure to parasitic infections, particularly multiple infections and active convulsive epilepsy (ACE), in five sites across sub-Saharan Africa. Methods and Findings A case-control design that matched on age and location was used. Blood samples were collected from 986 prevalent cases and 1,313 age-matched community controls and tested for presence of antibodies to Onchocerca volvulus, Toxocara canis, Toxoplasma gondii, Plasmodium falciparum, Taenia solium and HIV. Exposure (seropositivity) to Onchocerca volvulus (OR = 1.98; 95%CI: 1.52–2.58, p<0.001), Toxocara canis (OR = 1.52; 95%CI: 1.23–1.87, p<0.001), Toxoplasma gondii (OR = 1.28; 95%CI: 1.04–1.56, p = 0.018) and higher antibody levels (top tertile) to Toxocara canis (OR = 1.70; 95%CI: 1.30–2.24, p<0.001) were associated with an increased prevalence of ACE. Exposure to multiple infections was common (73.8% of cases and 65.5% of controls had been exposed to two or more infections), and for T. gondii and O. volvulus co-infection, their combined effect on the prevalence of ACE, as determined by the relative excess risk due to interaction (RERI), was more than additive (T. gondii and O. volvulus, RERI = 1.19). The prevalence of T. solium antibodies was low (2.8% of cases and 2.2% of controls) and was not associated with ACE in the study areas. Conclusion This study investigates how the degree of exposure to parasites and multiple parasitic infections are associated with ACE and may explain conflicting results obtained when only seropositivity is considered. The findings from this study should be further validated.

Premature mortality in active convulsive epilepsy in rural Kenya Causes and associated factors

Objective: We estimated premature mortality and identified causes of death and associated factors in people with active convulsive epilepsy (ACE) in rural Kenya. Methods: 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. Results: 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%. Conclusion: 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.

Clinical features, proximate causes, and consequences of active convulsive epilepsy in Africa.

Epilepsy is common in sub‐Saharan Africa (SSA), but the clinical features and consequences are poorly characterized. Most studies are hospital‐based, and few studies have compared different ecological sites in SSA. We described active convulsive epilepsy (ACE) identified in cross‐sectional community‐based surveys in SSA, to understand the proximate causes, features, and consequences.

The validation of a three-stage screening methodology for detecting active convulsive epilepsy in population-based studies in health and demographic surveillance systems

BackgroundThere are few studies on the epidemiology of epilepsy in large populations in Low and Middle Income Countries (LMIC). Most studies in these regions use two-stage population-based screening surveys, which are time-consuming and costly to implement in large populations required to generate accurate estimates. We examined the sensitivity and specificity of a three-stage cross-sectional screening methodology in detecting active convulsive epilepsy (ACE), which can be embedded within on-going census of demographic surveillance systems.We validated a three-stage cross-sectional screening methodology on a randomly selected sample of participants of a three-stage prevalence survey of epilepsy. Diagnosis of ACE by an experienced clinician was used as ‘gold standard’. We further compared the expenditure of this method with the standard two-stage methodology.ResultsWe screened 4442 subjects in the validation and identified 35 cases of ACE. Of these, 18 were identified as false negatives, most of whom (15/18) were missed in the first stage and a few (3/18) in the second stage of the three-stage screening. Overall, this methodology had a sensitivity of 48.6% and a specificity of 100%. It was 37% cheaper than a two-stage survey.ConclusionThis was the first study to evaluate the performance of a multi-stage screening methodology used to detect epilepsy in demographic surveillance sites. This method had poor sensitivity attributed mainly to stigma-related non-response in the first stage. This method needs to take into consideration the poor sensitivity and the savings in expenditure and time as well as validation in target populations. Our findings suggest the need for continued efforts to develop and improve case-ascertainment methods in population-based epidemiological studies of epilepsy in LMIC.

Prevalence and risk factors for active convulsive epilepsy in rural northeast South Africa

Highlights • Epilepsy is prevalent in rural South Africa, but less than other parts of Africa.• Most epilepsy starts in childhood.• Poor obstetric history and snoring were associated with active convulsive epilepsy.• HIV and parasitic infection were not associated with active convulsive epilepsy.