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Lymphatic filariasis patient identification in a large urban area of Tanzania: An application of a community-led mHealth system

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  • Upendo Mwingira
  • Maria Chikawe
  • Wilfred Lazarus Mandara
  • Hayley E Mableson
  • Cecilia Uisso
  • Irene Mremi
  • Alpha Malishee
  • Mwele Malecela
  • Charles D Mackenzie
  • Louise A Kelly-Hope
  • Michelle C Stanton
Article numbere0005748
<mark>Journal publication date</mark>14/07/2017
<mark>Journal</mark>PLoS Neglected Tropical Diseases
Issue number7
Number of pages17
Publication StatusPublished
<mark>Original language</mark>English
Externally publishedYes


BACKGROUND: Lymphatic filariasis (LF) is best known for the disabling and disfiguring clinical conditions that infected patients can develop; providing care for these individuals is a major goal of the Global Programme to Eliminate LF. Methods of locating these patients, knowing their true number and thus providing care for them, remains a challenge for national medical systems, particularly when the endemic zone is a large urban area.

METHODOLOGY/PRINCIPLE FINDINGS: A health community-led door-to-door survey approach using the SMS reporting tool MeasureSMS-Morbidity was used to rapidly collate and monitor data on LF patients in real-time (location, sex, age, clinical condition) in Dar es Salaam, Tanzania. Each stage of the phased study carried out in the three urban districts of city consisted of a training period, a patient identification and reporting period, and a data verification period, with refinements to the system being made after each phase. A total of 6889 patients were reported (133.6 per 100,000 population), of which 4169 were reported to have hydrocoele (80.9 per 100,000), 2251 lymphoedema-elephantiasis (LE) (43.7 per 100,000) and 469 with both conditions (9.1 per 100,000). Kinondoni had the highest number of reported patients in absolute terms (2846, 138.9 per 100,000), followed by Temeke (2550, 157.3 per 100,000) and Ilala (1493, 100.5 per 100,000). The number of hydrocoele patients was almost twice that of LE in all three districts. Severe LE patients accounted for approximately a quarter (26.9%) of those reported, with the number of acute attacks increasing with reported LE severity (1.34 in mild cases, 1.78 in moderate cases, 2.52 in severe). Verification checks supported these findings.

CONCLUSIONS/SIGNIFICANCE: This system of identifying, recording and mapping patients affected by LF greatly assists in planning, locating and prioritising, as well as initiating, appropriate morbidity management and disability prevention (MMDP) activities. The approach is a feasible framework that could be used in other large urban environments in the LF endemic areas.