Impact of the Stool-Based Xpert Test on Childhood Tuberculosis Diagnosis in Selected States in Nigeria.

BACKGROUND: In Nigeria, most children with tuberculosis (TB) present at primary health clinics where there are limited personnel skilled in collecting appropriate respiratory specimens from those who cannot produce sputum. KNCV Nigeria, in collaboration with the National Tuberculosis Control Program, implemented a modified simple, one-step (SOS), stool-based Xpert MTB/RIF method for diagnosis of TB in children who cannot expectorate sputum. We evaluated the impact of its implementation on childhood TB diagnosis. METHOD: A cross-sectional study was conducted across 14 selected states using secondary data of children presumed to have TB. Stool was collected from children presumed to have TB and processed using Xpert. RESULT: Out of 52,117 presumptive TB cases, 52% were male and 59.7% were under 5 years old. A total of 2440 (5%) cases were diagnosed with TB, and 2307 (95%) were placed on treatment. Annual TB notifications increased significantly after the introduction of the stool-based Xpert test when compared to those in the pre-implementation period. Increasing contributions from stool testing were observed throughout the implementation period, except in 2020 during the COVID-19 era. Overall, stool Xpert testing improved childhood TB notification in the studied states. Interventions aimed at awareness creation, capacity building, and active case finding improved the performance of the test.

Identifying Hot Spots of Tuberculosis in Nigeria Using an Early Warning Outbreak Recognition System: Retrospective Analysis of Implications for Active Case Finding Interventions.

BACKGROUND: Undiagnosed tuberculosis (TB) cases are the major challenge to TB control in Nigeria. An early warning outbreak recognition system (EWORS) is a system that is primarily used to detect infectious disease outbreaks; this system can be used as a case-based geospatial tool for the real-time identification of hot spot areas with clusters of TB patients. TB screening targeted at such hot spots should yield more TB cases than screening targeted at non-hot spots. OBJECTIVE: We aimed to demonstrate the effectiveness of an EWORS for TB hot spot mapping as a tool for detecting areas with increased TB case yields in high TB-burden states of Nigeria. METHODS: KNCV Tuberculosis Foundation Nigeria deployed an EWORS to 14 high-burden states in Nigeria. The system used an advanced surveillance mechanism to identify TB patients' residences in clusters, enabling it to predict areas with elevated disease spread (ie, hot spots) at the ward level. TB screening outreach using the World Health Organization 4-symptom screening method was conducted in 121 hot spot wards and 213 non-hot spot wards selected from the same communities. Presumptive cases identified were evaluated for TB using the GeneXpert instrument or chest X-ray. Confirmed TB cases from both areas were linked to treatment. Data from the hot spot and non-hot spot wards were analyzed retrospectively for this study. RESULTS: During the 16-month intervention, a total of 1,962,042 persons (n=734,384, 37.4% male, n=1,227,658, 62.6% female) and 2,025,286 persons (n=701,103, 34.6% male, n=1,324,183, 65.4% female) participated in the community TB screening outreaches in the hot spot and non-hot spot areas, respectively. Presumptive cases among all patients screened were 268,264 (N=3,987,328, 6.7%) and confirmed TB cases were 22,618 (N=222,270, 10.1%). The number needed to screen to diagnose a TB case in the hot spot and non-hot spot areas was 146 and 193 per 10,000 people, respectively. CONCLUSIONS: Active TB case finding in EWORS-mapped hot spot areas yielded higher TB cases than the non-hot spot areas in the 14 high-burden states of Nigeria. With the application of EWORS, the precision of diagnosing TB among presumptive cases increased from 0.077 to 0.103, and the number of presumptive cases needed to diagnose a TB case decreased from 14.047 to 10.255 per 10,000 people.

Asking people directly about preferred health-seeking behaviour yields invalid response: an experiment in south-east Nigeria.

BACKGROUND: Various factors determine health-seeking behaviour in south-east Nigeria. This study compared the hypothetical and actual health-seeking behaviour using where people sought malaria treatment as proxy for health-seeking behaviour and determinant of health service utilization. METHODS: The study was conducted in an urban area and a rural area in the Anambra state, south-east, Nigeria. Multistage sampling method was used to select a minimum sample size of 400 households in each community. Datawere collected on where people would prefer to be treated for malaria if they had malaria and where they actually sought for malaria treatment. RESULTS: Hypothetically majority of the people would prefer to use public and private hospitals for treatment of malaria but in reality majority of respondents in both rural and urban areas sought treatment at patent medicine dealers (PMDs) for both adult and childhood malaria. CONCLUSION: There were divergences between what people stated they would have ideally done in treating malaria and what they actually did when malaria occurred. Since PMDs were actually used by consumers of malaria treatment over other providers mainly because of low cost, there is the need to train PMDs to improve the quality of their services.

Are there geographic and socio-economic differences in incidence, burden and prevention of malaria? A study in southeast Nigeria.

RATIONALE: It is not clearly evident whether malaria affects the poor more although it has been argued that the poor bear a very high burden of the disease. This study explored the socioeconomic and geographic differences in incidence and burden of malaria as well as ownership of mosquito nets. METHODS: Structured questionnaires were used to collect information from 1657 respondents from rural and urban communities in southeast Nigeria on: incidence of malaria, number of days lost to malaria; actions to treat malaria and household ownership of insecticide treated and untreated mosquito nets. Data was compared across socio-economic status (SES) quartiles and between urban and rural dwellers. RESULTS: There was statistically significant urban-rural difference in malaria occurrence with malaria occurring more amongst urban dwellers. There was more reported occurrence of malaria amongst children and other adult household members in better-off SES groups compared to worse-off SES groups, but not amongst respondents. The average number of days that people delayed before seeking treatment was two days, and both adults and children were ill with malaria for about six days. Better-off SES quartile and urban dwellers owned more mosquito nets (p < 0.05) (treated and untreated). CONCLUSION: Malaria occurs more amongst better-off SES groups and urban dwellers in southeast Nigeria. Deployment of malaria control interventions should ensure universal access since targeting the poor and other supposedly vulnerable groups may exclude people that really require malaria control services.