| Literature DB >> 31185939 |
Paul Edward Okello1, Lilian Bulage2, Alex Ario Riolexus2, Daniel Kadobera2, Benon Kwesiga2, Henry Kajumbula3, Muhamed Mulongo4, Eunice Jennifer Namboozo5, Godfrey Pimundu5, Isaac Ssewanyana5, Charles Kiyaga5, Steven Aisu5, Bao-Ping Zhu6.
Abstract
BACKGROUND: A cholera outbreak started on 29 February in Bwikhonge Sub-county, Bulambuli District in Eastern Uganda. Local public health authorities implemented initial control measures. However, in late March, cases sharply increased in Bwikhonge Sub-county. We investigated the outbreak to determine its scope and mode of transmission, and to inform control measures.Entities:
Keywords: Cholera; Outbreak; Uganda
Mesh:
Substances:
Year: 2019 PMID: 31185939 PMCID: PMC6558808 DOI: 10.1186/s12879-019-4036-x
Source DB: PubMed Journal: BMC Infect Dis ISSN: 1471-2334 Impact factor: 3.090
Cholera attack rates by parish in Bwikhonge sub-county in Bulambuli district, March 2017
| Category | Cases ( | Population ( | Attack rate (%) |
|---|---|---|---|
| Sex | |||
| Male | 53 | 4042 | 1.3 |
| Female | 55 | 4362 | 1.3 |
| Age (years) | |||
| 5-12 | 20 | 1790 | 1.1 |
| 13-19 | 6 | 1437 | 0.41 |
| 20-30 | 30 | 1890 | 1.6 |
| 31-59 | 31 | 1681 | 1.8 |
| 60-90 | 21 | 345 | 6.1 |
| Parish | |||
| Bwikhonge | 83 | 2689 | 3.1 |
| Bulumera | 23 | 1849 | 1.2 |
| Bunalwere | 1 | 1597 | 0.063 |
| Buwabwala | 1 | 756 | 0.13 |
| Buwekanda | 0 | 1513 | 0 |
The attack rates were similar in males and females, all age groups were affected with the highest attack rate occuring in the elderly persons. Bwikhonge subcounty had the highest attack rate at 3 persons per 100
Fig. 1Epidemic curve of cholera outbreak in Bwikhonge sub-county in Bulambuli District, March 2016
Case control study: characteristics of cholera cases (N = 100) and controls (N = 100)
| Variable | Case n (%) | Control n (%) |
|---|---|---|
| Level of education of household head | ||
| None | 14 (14) | 18 (18) |
| Primary | 65 (65) | 61 (61) |
| Secondary | 21 (21) | 21 (21) |
| Level of education of case/control | ||
| None | 9 (9.2) | 16 (16) |
| Primary school | 69 (70.4) | 65 (65) |
| Secondary school | 20 (20.4) | 19 (19) |
| Occupation | ||
| Peasant farmer | 80 (80) | 77 (78) |
| Soldier/police officer | 1 (1) | 1 (1) |
| Pupil/student | 19 (19) | 22 (22) |
| Latrine availability | ||
| Available | 68 (69.4) | 75 (76) |
| Not available | 30 (30.6) | 24 (24) |
| Evidence of open defecation | ||
| Yes | 24 (25) | 10 (10) |
| No | 72 (75) | 86 (90) |
There was no notable difference between cases and controls in terms of level of education, and occupation. However, 31% of the cases did not have latrines compared to 24% for controls. Open defecation was observed among 25% of the case’s households compared to 10% for controls. Although latrine availability and open defecation do not directly cause cholera transmission, they point to hygiene problems in the community
Case-control study: risk factors for cholera due to water utility or drinking water from various water sources (n = 100 Cases, n = 100 controls)
| Variable | Cases | Controls | ORM-Ha | 95%CI |
|---|---|---|---|---|
| Untreated borehole water for drinking | ||||
| Yes | 35(36) | 54(54) | 0.31 | 0.13-0.65 |
| No | 63(64) | 46(46) | ref | |
| Untreated Cheptui river water for drinking | ||||
| Yes | 76(78) | 54(51) | 7.8 | 2.7-22.0 |
| No | 22(22) | 49(49) | ref | |
| Untreated swamp water for drinking | ||||
| Yes | 11(11) | 5(5) | 2.5 | 0.80-8.0 |
| No | 87(89) | 95(95) | ref | |
| Untreated borehole water for domestic utility | ||||
| Yes | 35(36) | 40(40) | 0.70 | 0.30-1.5 |
| No | 63(64) | 60(60) | ref | |
| Untreated Cheptui river water for domestic utility | ||||
| Yes | 81(83) | 69(69) | 3.8 | 1.4-10.0 |
| No | 17(17) | 31(31) | ref | |
| Untreated swamp water for domestic utility | ||||
| Yes | 12(12) | 3(3) | 5.5 | 1.2-25.0 |
| No | 86(88) | 97(97) | ref | |
aORM odds ratio of association was computed by stratification or Mantel-Haenszel method. Drinking untreated borehole water was protective, ORM-H = 0.31, 95% CI=0.13-0.65) and this result might be due to confounding factors in which persons may have used bore hole water with other water sources in various combinations. Water was drunk or used untreated (and unboiled) from all sources. People who drank untreated Cheptui river water were up to 8 times as likely to have had cholera compared to those who did not (ORM-H =7.8, 95% CI = 2.7-22.0) and this relatively larger ORM-H value supports the water borne hypothesis. People who used untreated Cheptui river water for routine work were up to 4 times as likely to have had cholera compared to those who did not (ORM-H =3.8, 95% CI = 1.4-13.0)