Clustering of pulmonary tuberculosis in Ethiopia: repeated population-based symptom screening

Abstract

AbstractObjectiveA “Cluster” is an area with a higher occurrence of tuberculosis than would be expected in an average random distribution of that area. Tuberculosis clustering is commonly reported in Ethiopia, but most studies rely on registered data, which may miss patients who do not visit health facilities or those who attend but are not identified as having tuberculosis. This makes the detection of actual clusters challenging. This study analysed the clustering of pulmonary tuberculosis and associated risk factors using symptom-based population screening in Dale, Ethiopia.DesgignA prospective population-based cohort study.SettingAll households in 383 enumeration areas were visited three times over 1 year period, at four-month intervals.ParticipantsIndividuals with pulmonary tuberculosis aged ≥15 years with demographic, socioeconomic, clinical, and geographic data residing in 383 enumeration areas (i.e., the lowest unit/village in the kebele, each with approximately 600 residents).Outcome measuresPulmonary tuberculosis (i.e., bacteriologically confirmed by sputum microscopy, GeneXpert or cluture plus clinically diagnosed pulmonary tuberculosis) and pulmonary tuberculosis clustering.ResultsWe identified pulmonary tuberculosis clustering in 45 out of the 383 enumeration areas. During the first round of screening, 39 enumeration areas showed pulmonary tuberculosis clustering, compared to only three enumeration areas in the second and third rounds. Our multilevel analysis found that enumeration areas with clusters were located farther from the health centres than other enumeration areas. No other determinants examined were associated with clustering.ConclusionsThe distribution of pulmonary tuberculosis was clustered in enumeration areas distant from the health centres. Routine systematic community screening using existing health infrastructure with Health extension workers may be costly but through targeted screening they can identify and refer persons with TB symptoms more quickly for diagnosis and treatment, thereby decreasing the duration of disease transmission and contributing to the reduction of TB burden.Stregths and limiations of this studyThe study applied a three-round total household symptom screening strategy to identify undiagnosed as well as diagnosed tuberculosis cases, and hence identify real clusters.Health extension workers actively involved the entire population in screening, benefitting from their trust and familiarity with the community.The study also sought for risk factors for clustering that may require attention from public health practices at the lowest community level.Smear microscopy will due to relatively low sensitivity always miss some cases of tuberculosis.