Fig 1.
Bangladesh high and low endemic districts by division.
Table 1.
District baseline prevalence of infection, year of training and patient searching, and population estimates.
Table 2.
Summary of data collection methods and costs in different endemic settings.
Table 3.
Number of community clinics per high endemic district, and number of upazila level Health Inspectors/Assistant Health Inspectors (HI/AHI), and community clinic staff trained.
Table 4.
Case numbers and prevalence rates of lymphoedema and hydrocoele by sex in 19 endemic districts.
Table 5.
Case numbers and prevalence rates of lymphoedema and hydrocoele by sex in 15 low endemic districts.
Table 6.
Mean upazila level case numbers, clinical prevalence rates per 100,000 and case-density rates per km2 for the high endemic divisions.
Fig 2.
Clinical case numbers, clinical prevalence per 100,000 and case density per square kilometre (km2) by upazila.
A. Lymphoedema case B. Lymphoedema prevalence C. Lymphoedema density km2 D. Hydrocoele cases E. Hydrocoele prevalence F. Hydrocoele density km2.
Fig 3.
The highest clinical prevalence and case density per km2, and overlapping hotspots by upazila in Rangpur Division.
A. High lymphoedema prevalence B. High lymphoedema density km2 C. Lymphoedema hotspots D. High hydrocoele prevalence E. High hydrocoele density km2 F. Hydrocoelehotspots.
Fig 4.
Distribution of lymphoedema and hydrocoele cases by upazila, sex, and age group.
A. Taraganj–lymphoedema B. Haripur–lymphoedema C. Baliadangi–lymphoedema D. Tatulia—lymphoedema E. Taraganj–hydrocoele F. Haripur–hydrocoele G. Baliadangi–hydrocoele H. Tatulia–hydrocoele.
Fig 5.
Proportion of mild, moderate and severe lymphoedema cases by upazila.
Fig 6.
Proportion of mild, mild and severe lymphoedema cases by age group and upazila.
A. Taraganj B. Haripur C. Baliadangi D. Tatulia.