Sociodemographic characteristics.

Background
Mozambique is one of the countries with the highest prevalence of schistosomiasis, although there is little data on the prevalence of disease and associated morbidity in the adult population. This study aimed to describe and characterize the morbidity associated with schistosomiasis in the adult population of Chókwè district and to explore the use of anamnestic questionnaires and urine dipsticks, as well as point-of-care ultrasound for urinary related findings, to better characterize disease prevalence and morbidity.
Methodology
Between April and October 2018, we conducted a cross-sectional study embedded within the Chókwè Health Research and Training Centre. Data were collected on sociodemographic variables, signs and symptoms for schistosomiasis and water related activities. Infection status was determined by urine filtration, Kato-Katz thick smear and DNA detection. Point-of care urinary tract ultrasonography was performed to assess structural morbidity associated with Schistosoma haematobium infection. Multivariate logistic regression was used to search for associations between risk factors, signs and symptoms, infection status and ultrasound abnormalities.
Principal findings
Our study included 1033 participants with a median age of 34 years old. The prevalence of Schistosoma haematobium, Schistosoma mansoni and ultrasound detected urinary tract abnormalities were 11.3% (95% CI 9.5%-13.4%), 5.7% (95% CI 4.3%-7.5%) and 37.9% (95% CI 34.8%-41.2%), respectively. Of the 37.9% with urinary tract abnormalities, 14.5% were positive for Schistosoma haematobium. Reported hematuria in the last month (p = 0.004, aOR 4.385) and blood in the urine dipstick (p = 0.004, aOR 3.958) were markers of Schistosoma haematobium infection. Reporting lower abdominal pain (p = 0.017, aOR 1.599) was associated with ultrasound abnormalities.
Conclusion
Using microscopy and DNA analysis for both Schistosoma haematobium and Schistosoma mansoni in conjunction with urinary ultrasound abnormalities gives us several insights into correlations between disease prevalence (microscopic and anatomical) and demographic details in a high-risk population.