XXXX prevalence in rural Zambia: a door-to-door survey.

@entity1 @entity410 @entity6583 @entity302 @entity311
OBJECTIVES: To identify @entity1 with @entity302 (PWE) in our Zambian catchment area of 55,000 @entity1 . METHODS: A nine-item, previously validated screening instrument for detecting @entity302 in developing countries was forward-and-back translated into Chitonga. Early piloting indicated poor specificity among @entity1 , so three questions were added. Local census data were used to estimate the population at risk. Community health workers conducted screening interviews with household heads. All positive screens were referred for physician assessment. A blinded neurologist assessed a randomly selected subset (100 positives, 50 negatives) to determine screening instrument characteristics. RESULTS: We identified 799 @entity1 with possible @entity302 (unadjusted prevalence 14.5/1000). The adapted instrument exhibited 86% specificity (adjusted prevalence 12.5/1000). False positives occurred primarily among @entity1 who had experienced multiple @entity311 -associated @entity410 . Age-specific rates were highest for @entity1 aged 5-15 years (26.2/1000) and for @entity1 over 65 years (15.9/1000). Males were disproportionately represented (55.8%vs. 44.2%, P<0.05), although this trend reversed after childbearing age. CONCLUSION: Even using a relatively conservative definition, we identified almost 700 PWE. Use of the recommended epidemiological definitions would likely have yielded higher prevalence rates. The age-specific prevalence did not follow patterns described where @entity6583 is the commonest cause of @entity302 . Trends in age- and gender-specific prevalence may offer a clue to the aetiology of @entity302 in this region.
