Hello,
I’m a PhD candidate in Public Health. I recently concluded my course work and hit a massive brick wall with my research. My focus is on a Neglected Tropical Disease called schistosomiasis in Chad. See topic and details below:
Characterization of Behavioral and Environmental Determinants of Schistosomiasis in Chad.
The history of human schistosomiasis (SCH) in Chad dated back as far as the 1960s and 1970s Chad (Rollinson et al., 2013).
The population exposed to schistosomiasis has evolved over the years in Chad. By 1977, 85.8% (3,600,000/ 4,197,000) of the Chadian population was at risk of human schistosomiasis (Iatroski and Davis, 1981).
That number became 79% in 1989 (Utroska et al., 1989) and in 1995 (Chitsulo et al., 2000). Moving to 2010, epidemiological data revealed of the 11,715,000 Chadians, 4,997,975 were infected with schistosomiasis, correlating to an estimated countrywide prevalence of 42.7% (Rollinson et al., 2013).
• Current estimates from the Expanded Special Project for Elimination of Neglected Tropical Diseases (ESPEN) shows that up to 51.31 (9,779,529 /19,060,615) of Chadians are at risk of schistosomiasis infection (ESPEN, 2024).
• Three species have been identified so far. S. haematobium is highly endemic, S. mansoni is mildly endemic and only occurred within the S. haematobium range and S.guineensis has also been reported (Knight, 2015).
- According to the World Health Organization (WHO) the endemicity of SCH is classified in four categories:
- Non-endemic (prevalence <1% )
- Low endemic (prevalence ≥1% and <10%)
- Moderate endemic (prevalence ≥10% and <50%)
- High (prevalence ≥50%), by implementation unit (WHO, 2022).
However, due to funding restrictions and insecurity in Chad, of the 107 implementation units endemic to SCH, only 59 (55.1%) districts across 8 provinces (Chari Baguirmi, Logone Occidental, Logone Oriental, Mayo Kebbi Est, Mayo Kebbi Ouest, Moyen Chari, Mandoul and Tandjile ) have effectively implemented MDA against SCH.
This is partly because these regions are fairly more secure and partially due to the fact these IUs are co-endemic with Onchocerciasis and lymphatic filariasis, making it feasible to deliver integrated interventions (ESPEN, 2024).
Context and justification of impact assessment
- According to the monitoring and evaluation requirements of WHO, impact evaluation through parasitological assessments is required after five effective rounds of mass treatment. Meaning, health districts which have attained the WHO minimum MDA coverage threshold of 75% after five consecutive rounds of should undertake impact assessment (WHO, 2022).
- On this premise, 25 health districts which had completed five effective rounds of SCH MDA but didn’t have any subdistrict epidemiological data due to the fact they were split from their parent health district during the revision of the health map by the Ministry of Health were prioritized and subjected to impact assessment from November 2022-April 2023 (Ministry of Health, 2023).
- In addition, WHO is strongly recommending that Schistosomiasis Control Programmes implement MDA at subdistrict level due to the high focality of the disease, as district-based data do not effectively reflect subdistrict endemicity (WHO, 2022). Hence 248 subdistricts across 25 districts were surveyed, ensuring that each subdistrict had at least one sentinel site (Ministry of Health 2022).
- The aim of the survey was to measure the impact of mass drug administration for SCH and establish baseline endemicity for SCH in 25 districts and 2 subdistricts in Logone Occidental, Logone Oriental, Mayo Kebbi Est, Mayo Kebbi Ouest, Moyen Chari, Sila, Mandoul and Tandjile regions without mapping points.
The objectives were to:
- Assess health outcomes after 5 effective rounds of SCH MDA by measuring the prevalence and intensity of SCH infection amongst SAC in 248 subdistricts across 25 health districts;
- Establish the baseline prevalence of SCH among school aged children (SAC) in 25 districts and 248 subdistricts;
- Measure indicators relating to water, sanitation and hygiene (WASH).
Methods
• Given the high focality of SCH, purposive sampling via field pre-visits was done to identify survey sites (schools).
• 1-3 survey points (schools) per subdistrict were purposefully identified
• 264 subdistricts were targeted across 25 health districts but 16 subdistricts were not reached due to insecurity.
• SAC 6-14 years were sampled via systematic sampling
• Kato-Katz and urine filtration techniques were used to identify parasites.
Key Findings
• 94.2% (308 out of 327) of schools were investigated across 248 health areas or sub-districts spanning 25 districts in 7 provinces.
• 16,104 school-aged children (6 to 14 years) participated in the study, with 8,061 girls (50.05%) and a mean age of 6.25 (± 2.7) years.
• Among the 308 schools investigated, more than half had undergone mass treatment in the six months preceding the mapping survey.
• 199 schools (64.61%) received albendazole/mebendazole, while 201 schools (65.26%) were treated with praziquantel.
• 16 were not included in the mapping, primarily due to insecurity arising from tribal conflicts. Additionally, some areas were situated in close proximity to conflict zones in the Central African Republic, further complicating the mapping process.
• The overall prevalence of Schistosoma mansoni was 0.74%, while Schistosoma haematobium had a prevalence of 5.36%.
• Among the 118 children infected with S. mansoni, 68 (57.63%), 37 (11.02%), and 13 (31.36%) were mildly, moderately, and heavily infected, respectively. While for S. haematobium, of the 858 infected children, respectively, 648 (75.52%) and 210 (24.48%) were weakly and heavily infected.
• Overall, regardless of the level of intervention considered (district, subdistrict or school), the prevalence of each of the three STH species, and even when combined, was consistently < 5% for more than two-thirds of the cases.
• The predominant STH species was Ascaris lumbricoides. The intensities of infections due to STH were all low regardless of the parasite considered. This implies the 102,142 SAC in Pont Carol, Korbol and Balimba health districts which were classified as moderately endemic at baseline, thus needing yearly STH MDA won’t be treated anymore going forward.
Prevalence Change by District
- There was a consistent decline in the prevalence of schistosomiasis across the 25 health districts involved in the survey.
• High achieving areas:
o The most significant declines were observed in the Kolon health district (-65.37%), followed by Guelo (-54.02%), Guegou (-53.94%), and Lagon (-52.24%). Notably, these health districts all transitioned from high risk (≥50%) to low risk (≥1% and <10%).
• Low achieving areas:
o In contrast, three districts experienced a surge in prevalence, with the most significant increases observed in Moulkou (+12.63%) and Youe (+12.54%), both of which moved from low risk to moderate risk (≥10% and <50%). Additionally, Gagal saw a marginal increase (+2.23%) but remained within the low-risk category.
Note: The impact of a control programme is measured by its ability to attain elimination of SCH as a public health problem. Therefore, for a programme to attain elimination of SCH as a public health problem, prevalence of heavy-intensity infections in school-aged children (5-14 years) should be < 1% in all endemic districts (WHO, 2022).
• Seven health districts (Binder, Bongor, Fianga, Guegou, GUELO, Kolon, and Lagon), initially classified as high risk (prevalence ≥50%), have shifted to moderate risk (Binder, Bongor, Fianga) and low risk (Guegou, GUELO, Kolon, and Lagon).
• This adjustment represents 66,640 SAC and 98,959 SAC, respectively, requiring yearly and once-in-two-years MDA.
• Tissi health district with an unknown endemicity at baseline was classified as moderately endemic, hence 10,530 SAC would require yearly MDA.
• Conversely, Moulkou and Youé districts transitioned from low risk to moderate risk, necessitating yearly treatment instead of once-in-two-years. As a result, 26,365 SAC will now require annual MDA in these districts. This is considered as treatment failure.
• When considering the subdistrict as the implementation unit, 73 (29.4%) out of the 248 surveyed no longer require MDA, resulting in 184,965 SAC who do not need PZQ treatment.
• Amongst these 73 subdistricts, 11 (15.1%) were previously categorized as low risk, 45 (61.6%) as moderate risk, 16 (21.9%) as high risk, while 1 (1.4%) subdistrict had unknown endemicity at baseline.
• In total, 122 subdistricts (49.2%) would require MDA every two years, accounting for 336,065 SAC. Amongst these, 26 (21.3%) were categorized as low risk at baseline, 52 (42.6%) as moderate risk, 37 (30.3%) as high risk, and 7 (5.7%) had unknown endemicity.
• 50 subdistricts (20.2%) require annual treatment, representing 128,019 SAC. At baseline, 12 (24%) of these subdistricts were low risk, 10 (20%) were moderate risk, 24 (48%) were high risk, and 4 (8%) had unknown endemicity.
• 3 subdistricts (1.2%) previously classified as low risk at baseline would require biannual MDA, involving 5,236 SAC going forward.
Potential Research Question
· What are the determinants of schistosomiasis transmission characterizing health outcomes (disease prevalence) across 25 districts in the Logone Occidental, Logone Oriental, Mayo Kebbi Est and Pont Carol Provinces of Chad after more than five years of mass drug administration (MDA).
Objectives
• To characterize ecological determinants of SCH transmission across the districts surveyed.
• To determine factors influencing better and poor programmatic outcomes across health districts.
• To identify sociodemographic variable influencing/associated with the prevalence and intensity of schistosomiasis infections
Task Expected:
1. Merge the 2022/2023 epidemiological survey data with the 2015 DHS data
2. Conduct Data analysis using SPSS or STATA, using but not limited to the below variables, to understand what sociodemographic factors are potentially responsible to high achieving and low achieving districts. DHS data will be useful for shed light on the desired outcomes.
a. Demographic Variables
- Gender: Analyze gender-specific differences in prevalence, as boys and girls may have distinct exposure patterns due to their roles and activities.
- Family size and structure: Consider household composition, which may influence health-seeking behaviors and access to interventions.
b. Socioeconomic Variables
- Education level: Education of caregivers or guardians and children impacts awareness about disease prevention and access to treatment.
- Income level: Household income influences access to clean water, healthcare, and ability to adopt protective measures.
- Occupation: Jobs related to water, such as fishing or agriculture, increase exposure risk.
c. Environmental Variables
- Proximity to water bodies: Distance to rivers, lakes, or ponds is a critical determinant of exposure risk.
- Housing conditions: Quality of housing, particularly access to clean water and sanitation facilities, is crucial.
d. Behavioral Variables
- Water contact activities: Frequency and type of water-related activities (bathing, swimming, or irrigation) directly affect exposure risk.
- Hygiene practices: Handwashing, bathing practices, and defecation habits in or near water sources.
- Healthcare-seeking behavior: Patterns of seeking treatment for symptoms and access to medical care.
e. Cultural and Social Factors
- Beliefs and practices: Cultural perceptions about disease causation and traditional treatment methods.
- Community practices: Shared behaviors, such as communal bathing in rivers or ponds, that may influence transmission.
f. Accessibility and Equity Variables
- Healthcare access: Distance to healthcare facilities and availability of medications like praziquantel.
- Health education access: Exposure to programs promoting schistosomiasis prevention and control.
- Intervention coverage: Whether mass drug administration (MDA) campaigns have reached certain demographic groups.
g. Suggestions from Essay Pro
3. Write out the workflow of the analysis process and data visualization reports for replicability.
4. Determine the theoretical framework of interest most
5. Review the research question/hypothesis and research objectives
6. Determine the most appropriate theoretical framework of interest
7. Review the draft research question and objectives, and make proposals for amendment.
8. Following the final agreed research question, advice on additional analysis based on your experience to strengthen the research idea.