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Knowledge and practices of households on safe water chain maintenance in a slum community in Kampala City, Uganda

  • Charles SsemugaboEmail author
  • Solomon Tsebeni Wafula
  • Rawlance Ndejjo
  • Frederick Oporia
  • Jimmy Osuret
  • David Musoke
  • Abdullah Ali Halage
Open Access
Research article
  • 113 Downloads

Abstract

Background

More than half of the disease burden in Uganda can be prevented through improving water, sanitation, and hygiene (WASH). In slum communities, water supply is insufficient but also highly contaminated; therefore, ensuring that the safe water chain is maintained by households is paramount to preventing water-related diseases. This study aimed at assessing knowledge and practices of households on safe water chain maintenance in slum communities in Kampala City, Uganda.

Methods

This was a community-based cross-sectional study carried out among 395 households in slum communities in Kampala, Uganda. Data were collected using a semi-structured questionnaire. Prevalence ratios (PRs) and their 95% confidence intervals were used as a measure of association between safe water chain management and associated knowledge and practice factors. The PRs were obtained using a multivariable modified Poisson regression with logarithm as the link function, with robust standard errors.

Results

Majority (76.7%, 303/395) of the households collected their water from a piped water system and paid for the water (72.9%, 288/395). Almost all (97.2%, 384/395) of the participants said that they knew the dangers associated with drinking unsafe water, boiled their drinking water (95.4%, 377/395), and used storage containers that minimize contamination (97.0%, 383/395). However, only (32.4%, 128/395) of the households satisfactorily maintained the safe water chain. Female- (adjusted PR = 1.82, 95% CI (1.19–2.78)) and student-led households (adjusted PR = 1.58, 95% CI (1.03–2.41)) and those whose heads had attained post-primary education (adjusted PR = 1.48, 95% CI (1.02–2.17)) were more likely to satisfactorily maintain the safe water chain. This was similar among members who thought most contamination occurs during storage (adjusted PR = 1.47, 95% CI (1.10–1.97)).

Conclusion

Only a third of the households maintained the safe water chain satisfactory. Female-led, student-led, and post-primary educated-led household and household that thought most contamination occurs during storage were more likely to maintain the safe water chain. There is a need to improve the level of awareness about the importance of the safe water chain among slum dwellers.

Keywords

Safe water chain Maintenance Households Slum Uganda 

Abbreviations

NWSC

National Water and Sewerage Cooperation

PRs

Prevalence ratios

UBOS

Uganda Bureau of Statistics

WASH

Water, sanitation, and hygiene

Background

Adequate water, sanitation, and hygiene (WASH) is essential to ensure good health and wellbeing. In fact, 85% of the disease burden in Africa could be prevented through improved WASH [1]. Indeed, through improvements in WASH, 502,000, 280,000, and 297,000 deaths due to inadequate drinking water, sanitation, and poor hand hygiene respectively could be averted [2]. Specifically, interventions aimed at improving water quality have been associated with diarrhea and infectious disease reductions [3, 4]. This notwithstanding, many countries including Uganda are still grappling with challenges related to water access with 663 million people in the world estimated to lack access to improved water supplies, half of whom are in sub-Saharan Africa [5]. The situation is worse in slum areas which are usually characterized by inadequate access to water and thus a high burden and episodic outbreaks of WASH-related infections such as typhoid fever, cholera, and dysentery [6, 7, 8]. Another key indicator of water supply is water quality, and studies in slum settings found high levels of contamination attributed to inappropriate technology and practices for poor waste disposal [9, 10, 11]. Therefore, in addition to ensuring access to safe water particularly in slums, similar efforts should be made to ensure that the provided water is of good quality through maintaining the safe water chain.

Safe water chain includes all processes involved in ensuring that water is not contaminated through all stages from the water source to consumption. Key stages in the safe water chain include water collection, handling, transportation, storage and treatment, and consumption. Although interventions focused on improving household water quality such as improving water storage or treatment have registered positive outcomes in terms of disease reduction [12, 13], measures may not be readily accessible by most households in slums. This further emphasizes the importance of taking practicable measures to avoid water contamination along the water chain. Also, knowledge of communities about safe water chain maintenance interventions and the extent to which they are practiced is important in planning feasible and effective intervention for slum settings. In addition, previous studies in slum settings have shown deficiency in knowledge on WASH among community members [11, 14].

In Kampala, 53.6% of the urban population live in slum settings [15]. Majority of the households in Kampala slums collect their drinking water from the piped water system, regarded as safe, provided by National Water and Sewerage Corporation (NWSC) [16]. However, disease trends in Kampala slums portray them as prone to diarrheal disease outbreaks [7] including a 2014 reported outbreak of typhoid attributed to consumption of contaminated water [17]. These diarrheal disease outbreak occurrences are influenced by household safe water chain practices. This study therefore assessed knowledge and practices of households on safe water chain maintenance in slum communities in Kampala City, Uganda.

Methods

Study design and setting

This was a community-based cross-sectional study that used an interviewer-administered semi-structured questionnaire to collect data from household heads or other adults regarding maintenance of the safe water chain. The study was carried out in Kasubi slum, one of the many slums in the outskirts of Kampala, Uganda’s capital city [18]. A slum is defined as a heavily populated urban informal settlement where the inhabitants are characterized by substandard housing and low standard of living [19]. Kasubi parish comprises of mainly informal and substandard housing with a few businesses. It has an estimated population of 384,386 people translating to about 11,372 people/km2 spread across its 9 zones [20]. The major sources of water for residents in Kasubi are water taps (stand pipes) with a fee attached for water collection and springs. We purposively selected Kasubi parish due to high population density, uneven terrain, and poor sanitation and hygiene conditions in addition to its close proximity to the central business center of Kampala, hence likely to experience challenges in observing the safe water chain.

Sample size and sampling procedure

Using the formulae for cross-sectional studies [21], and assuming an alpha of 0.05, power (1-beta) of 0.80, a sampling error of 5%, a non-response rate of 5%, and a statistically conservative prevalence of 50% for households that do not maintain the safe water chain, a final sample size of 401 households was obtained. The 50% prevalence of households which did not maintain the safe water chain was used to obtain an unbiased sample because previous studies carried out in this area were not focused on maintenance of the safe water chain [22, 23, 24]. This sample size was distributed proportionately across the six selected zones out of the nine in Kasubi parish based on population size. The number of households in each zone was obtained from Lubaga division offices, and sampling proportionate to size was used to obtain the number of target households from each zone (Table 1). Households, defined by the Uganda Bureau of Statistics (UBOS) as a group of persons who normally live and eat together [25], were selected using systematic random sampling. The number of households in each zone was divided by the number of households to be selected from each zone to create a sampling interval. Within each zone, the first household was selected randomly. Subsequent households were selected by skipping a number of households equivalent to the sampling interval calculated based on the population of the selected zone (Table 1) until the sampled number of households in that zone was achieved.
Table 1

Sample size distribution across the zones

Zone

Total number of households

Sampled households per zone

Kawaala 1

3500

100

Kasubi zone 1

2000

64

Kasubi zone 3

2800

84

Kawaala 2

2400

67

Kasubi zone 4

1700

50

Kasubi zone 2

1600

36

Data collection

Data were collected using an interviewer-administered semi-structured questionnaire. We asked respondents about their sources of domestic water, knowledge on safe water chain, and maintenance of safe water chain. The questionnaire was developed based on reviewed literature on safe water chain [26, 27, 28, 29, 30, 31]. Data collection tools were pretested in Mulago slum within the city which had similar characteristics with the study area. Trained research assistants who were Environmental Health Students of Makerere University collected the data from all selected households.

Data management and analysis

Data were examined and cleaned daily during collection for completeness and entered in EpiData version 3.02 (EpiData association; Denmark). We used Stata 13.0 (Statacorp Texas; USA) for analysis. To determine the status of safe water chain maintenance (outcome variable), which was classified as either high maintenance or low maintenance, nine questions were asked on practices on safe water chain maintenance with responses “Yes” assigned 1 and “No” assigned 0 during analysis. Respondents who had a total score of at least 7 of the 9 were considered to have high maintenance of safe water chain practices and the rest otherwise. Prevalence ratios (PRs) computed using a generalized linear model of the Poisson family with the logarithm as the canonical link function, with robust standard errors while applying a forward elimination method, were used to measure the association between the outcome and independent variables. PRs were used instead of odds ratios since the prevalence of the outcome variable was > 10%, yet logistic regression’s odds ratios tend to overestimate the relative risk in such instances [32, 33]. Simple models consisting of the outcome and one independent variable were run to obtain the crude PRs. In the multivariable model, variables that had p values of up to 0.1 were included. The crude and the adjusted PRs and their corresponding 95% confidence intervals are presented.

Ethical considerations

Ethical approval for the study was obtained from the Makerere University School of Public Health Higher Degrees, Research and Ethics Committee (101). The study was also approved by Uganda National Council of Science and Technology registration (HS 867). Participation in the study was voluntary, and household heads or other consenting adults provided written informed consent.

Results

Sociodemographic characteristics of participants

A total of 395 households participated in the study out of the 401, resulting in a response rate of 98.5%. Majority of the participants were females (75.9%, 300/395) and Christians (77.5%, 306/395), had attained post-primary education (69.1%, 273/395), and aged 18–29 years (63.3%, 250/395). Most (38.5%, 152/395) household heads were engaged in business (Table 2).
Table 2

Sociodemographic characteristics of participants

Variables

Frequency (n = 395)

Percentage

Gender

 Female

300

75.9

 Male

95

24.1

Age (years) [mean (± SD)]

30.0 (10.8)

 

 18–29

250

63.3

 30–45

104

26.3

 ≥ 46

41

10.4

Education level

 None or primary

122

30.9

 Post-primary

273

69.1

Marital status

 Single

148

37.5

 Married

207

52.4

 Widowed/separated/divorced

40

10.13

Religion

 Christian

306

77.5

 Muslim

89

22.5

Occupation

 Business

152

38.5

 Unemployed

103

26.1

 Formal employment

49

12.4

 Student/pupil

45

11.4

 Farming

46

11.7

Household size

 1–3

174

44.0

 4–6

162

41.0

 ≥ 7

59

15.0

Sources and institutional aspects of domestic water

Majority (76.7%, 303/395) of the households used piped water as their source of water for domestic purposes, whereas only (23.3%, 92/395) obtained water from springs. All households were located within 500 m to the nearest water source, with (70.4%, 278/395) of the participants moving a distance of less 20 m to collect water. Only (25.1%, 99/395) of the households obtained water from communally owned sources. Most (61.5%, 243/395) households had daily water per capital utilization of less than 40 l and a large proportion (72.9%, 288/395) of participants paid money to collect water. Among the communal water sources, more than half (53.5%, 53/99) had water user committees (Table 3).
Table 3

Sources of domestic water and their maintenance

Variables

Frequency (N = 395)

Percentage

Main water source

 Piped water

303

76.7

 Springs

92

23.3

Estimated distance to nearest water source (meters)

 ≤ 20 (within the compound)

278

70.4

 21–100

85

21.5

 101–500

32

8.1

Water obtained from communally owned source

 No

296

74.9

 Yes

99

25.1

Water user committee for communal sources present (n = 99)

 Yes

53

53.5

 No

27

27.3

 Do not know

19

19.2

Water consumption per person per day (liters)

 ≤ 40

243

61.5

 > 40

152

38.5

Paid for water

 Yes

288

72.9

 No

107

27.1

Paid towards maintenance of main water source

 No

368

93.2

 Yes

27

6.8

Knowledge on water safety and its importance

Half (50.1%, 198/395) of the study participants said they knew that most contamination of water occurred at the water source. When asked whether they knew the dangers associated with drinking unsafe water, majority (97.2%, 384/395) of the participants said they did and (61.8%, 244/395) indicated that boiling drinking water was key to preventing diarrheal diseases (Table 4).
Table 4

Knowledge on water safety and its importance

Variables

Frequency (N = 395)

Percentage

Contamination of water occurs

 At the source

198

50.1

 During storage (storage container)

117

29.6

 During use

49

12.4

 Do not know

31

7.9

Safe water is

 Water that is clear

221

56.0

 Boiled water

89

22.5

 Water that has no germs

55

13.9

 Did not know

30

7.6

Said they knew dangers of drinking unsafe water

 Yes

384

97.2

 No

11

2.8

Benefits of drinking safe water

 Prevents disease

370

94.4

 Others (saving money, improving work efficiency)

10

2.5

 Did not know

15

3.8

Preventive measures for diarrheal diseases

 Drinking boiled water

244

61.8

 Keeping good personal hygiene

38

9.6

 Eating well-cooked food

26

6.6

 Washing hands with soap before eating food

23

5.8

 Others*

30

7.6

 Did not know

34

8.6

*Other preventive measures included bathing regularly, washing food, and proper waste disposal

Maintenance of safe water chain by households

Majority of the households used appropriate water collection containers such as jerry cans or pots (97.0%, 383/395). Majority of these water collection containers were clean (81.0%, 320/395). In addition, almost all (95.4%, 377/392) participants said they boiled their water to make it safe for drinking. Most households used storage containers which were covered (88.6%, 350/395) and clean (95.4%, 377/395). However, only (32.4%, 128/395) maintained the proper safe water chain practices (Table 5).
Table 5

Practices on safe water chain maintenance

Variables

Frequency (n = 395)

Percentage

Used water collection container that minimizes contamination1

 Yes

383

97.0

 No

12

3.0

Water collection container clean1

 Yes

320

81.0

 No

75

19.0

Methods of drinking water treatment^

 Boiling

377

95.4

 Chlorination

16

4.1

 Filtration

09

2.3

 Do not treat water

11

2.8

Method of water treatment appropriate1

 No

13

3.3

 Yes

382

96.2

 No

45

11.4

 Yes

350

88.6

Water storage container clean1

 No

18

4.6

 Yes

377

95.4

Cleaned drinking water storage containers at least once a week1

 Yes

108

27.3

 No

287

72.7

Cleaned water storage containers by scrubbing and rinsing1

 No

174

44.0

 Yes

221

56.0

Used a separate cup or container to draw drinking water from storage containers1

 No

329

83.3

 Yes

66

16.7

Maintenance of safe water chain (mean score, SD)

6.91 ± 1.28

 

 Low (scores < 6.91)

267

67.6

 High (scores ≥ 6.91)

128

32.4

1Variables used in determining average safe water chain practice scores

^Multiple options

Factors associated with maintenance of the safe water chain

The proportion of households with high maintenance of safe water chain practices was higher among female-led households (adjusted PR = 1.82, 95% CI (1.19–2.78)) and those whose heads had attained post-primary education (adjusted PR = 1.48, 95% CI (1.02–2.17)) and those that were student-led (adjusted PR = 1.58, 95% CI (1.03–2.41)) when compared with their counterparts. Households whose heads thought that most contamination occurred during storage were 50% (adjusted PR = 1.47, 95% CI (1.10–1.97)) more likely to maintain safe water chain practices compared to those who thought it occurred at the water source (Table 6).
Table 6

Factors associated with maintenance of the safe water chain

Characteristic (categories)

Safe water chain maintenance

Crude PR (95% CI)

p value

Adjusted PR (95% CI)

p value

Yes, n (%)

No, n (%)

Socio-economic factors

 Gender

  Male

20 (21.1)

75 (78.9)

1

 

1

 

  Female

108 (36.0)

192 (64.0)

1.71 (1.13–2.56)

0.012*

1.82 (1.19–2.78)

0.005*

 Age (years)

  14–29

90 (36.0)

160 (64.0)

1

 

1

 

  30–45

27 (26.0)

77 (74.0)

0.72 (0.50–1.04)

0.079

0.84 (0.59–1.22)

0.377

  > 45

11 (26.8)

30 (73.2)

0.75 (0.44–1.27)

0.279

1.06 (0.62–1.81)

0.842

 Education level

  None/primary

27 (22.1)

95 (77.9)

1

 

1

 

  Post-primary

101 (37.0)

172 (63.0)

1.67 (1.16–2.41)

0.006*

1.48 (1.02–2.17)

0.041*

 Marital status

  Single

51 (34.5)

97 (65.5)

1

   

  Married

68 (32.9)

139 (67.2)

0.95 (0.71–1.28)

0.751

  

  Widowed/divorced/separated

9 (22.5)

31 (77.5)

0.65 (0.35–1.21)

0.176

  

 Occupation

  Business

40 (26.3)

112 (73.7)

1

 

1

 

  Unemployed

33 (32.0)

70 (68.0)

1.21 (0.83–1.79)

0.320

1.13 (0.78–1.64)

0.528

  Salaried work

20 (40.8)

29 (59.2)

1.55 (1.01–2.38)

0.045*

1.41 (0.94–2.12)

0.098

  Student

21 (46.7)

24 (53.3)

1.77 (1.18–2.67)

0.006*

1.58 (1.03–2.41)

0.034*

  Farming

14 (30.4)

32 (69.6)

1.16 (0.69–1.93)

0.578

1.22 (0.73–2.05)

0.453

 Number of people in the household

  1–3

52 (29.9)

122 (70.1)

1

   

  4–6

54 (33.3)

108 (66.7)

1.12 (0.81–1.52)

0.497

  

  ≥ 7

22 (37.3)

37 (62.7)

1.24 (0.83–1.86)

0.281

  

Water source-related and individual factors

 Main water source used by household

  Piped water

99 (32.7)

204 (67.3)

1

   

  Springs

29 (31.5)

63 (68.5)

0.96 (0.69–1.36)

0.837

  

 Water from communally owned source

  No

102 (34.5)

194 (65.5)

1

   

  Yes

26 (26.3)

73 (73.7)

0.76 (0.53–1.10)

0.146

  

 Estimated distance to water source (meters)

  ≤ 20 (within the compound)

94 (33.8)

184 (66.2)

1

   

  21–100

23 (27.1)

62 (72.9)

0.80 (0.54–1.18)

0.258

  

  101–500

11 (34.4)

21 (65.6)

1.02 (0.61–1.68)

0.949

  

 Water consumption per person per day (liters)

  ≤ 40

72 (29.6)

171 (70.4)

1

   

  > 40

56 (36.8)

96 (63.2)

1.24 (0.94–1.65)

0.134

  

 Paid for water collection/fetching

  No

41 (38.3)

66 (61.7)

1

   

  Yes

87 (30.2)

201 (69.3)

0.79 (0.59–1.06)

0.118

  

 Perception of where most contamination occurred

  At the source

58 (29.3)

140 (70.7)

1

 

1

 

  During storage (jerry can/container)

53 (45.3)

64 (54.7)

1.55 (1.15–2.08)

0.004*

1.47 (1.10–1.97)

0.009*

  At point of use

10 (20.4)

39 (79.6)

0.70 (0.38–1.26)

0.233

0.69 (0.39–1.22)

0.197

  Did not know

7 (22.6)

24 (77.4)

0.77 (0.39–1.53)

0.458

0.79 (0.41–1.52)

0.475

Level of confidence = 95%; gender, age, education, and occupation were the potential confounders for safe water chain maintenance

PR prevalence ratio, CI confidence interval

*p < 0.05

Discussion

This study assessed knowledge and practices of households on safe water chain maintenance in households in Kasubi slum in Kampala, Uganda. Our findings show that the major sources of domestic water were private tap stands and protected springs. Most of the households paid for water, treated their water for drinking by boiling, and knew the sources of water contamination and dangers of drinking contaminated water. However, only a third of the households reported practices that maintain the safe water chain. Household heads who were females and students and/or attained post-primary education were more likely to maintain the safe water chain. Household heads who said that most contamination of water happens during storage were also more likely to maintain the safe water chain.

The major sources of domestic water in our study were private taps (71.6%) and protected springs (20.5%). The use of private tap stands is not surprising because many areas within the city including slums in Kampala are supplied with piped water from NWSC, a government agency responsible for treatment and distribution of water to the public. Similar studies done in Ghana and India have also found tap stands as a popular water source in slums [34, 35]. Slums most likely occur in low lying areas were protected springs are usually located. Protected springs and tap water are generally considered improved water sources and are therefore expected to provide relatively good quality water [36]. However, recent studies in Kampala showed that most protected springs were contaminated [10, 37]. Most households paid water bills which is expected in an urban setting since majority are connected to piped water which are metered and paid for by the final consumer.

From our study, most of the household heads knew the different ways by which water could get contaminated. Majority of respondents also knew the dangers of drinking contaminated water such as increased risk of diarrheal diseases. Since slums in Kampala have in the past experienced frequent outbreaks of diarrheal diseases especially cholera and typhoid [38], the high level of knowledge could be attributed to the intense awareness campaigns that are conducted whenever these outbreaks occur. In our study, only one third of the households maintained safe water chain management practices. This implies that two thirds of the population in slums in Kampala are at risk of drinking unsafe water and acquiring diarrheal diseases due to lack of maintenance of the safe water chain. Our findings corroborate with findings from a study in India where majority of the urban population did not observe safe water chain practices [39]. Therefore, there is a need to increase slum communities’ awareness on maintenance of the safe water chain.

Most households used collection and storage containers that would minimize contamination which is a good practice. However, few households were cleaning their containers regularly. In addition, most of the containers were not covered, and only a few households used a separate cup to draw drinking water from the containers (16.7%). This practice is sometimes discouraged with preference for small-mouthed containers. Educating people about the risk and pathways of water contamination can help improve water quality and consequently mitigate risks of diarrheal diseases. Another finding from our study is that boiling was the most common method of treatment of drinking water. This finding is similar to that from another Ugandan study that established that majority (89%) of the households were boiling their drinking water [40]. Boiling is known to be the most popular water treatment method especially in low-income countries [41]. It is a reliable treatment method against microbial agents if well used, and water thereafter well stored [41, 42]. Practicing such simple and cheap interventions at household level can lead to an improvement in the quality of drinking water which eventually leads to reduction in diarrheal diseases [43].

Female-headed households were more likely maintain safe water chain management practices. Our finding is in line with a study conducted in Cameroon which indicated that female-headed households were more likely to invest in the effort of fetching clean water and ensuring proper storage [43]. It has also been shown that women often engage in water collection, storage and treatment, and use compared to men in communities especially in slums [44, 45]. Women are at higher risk of water-borne and water-based infections such as diarrhea, ascariasis, and trichuriasis than men, as such observing high standards of safe water chain to minimize water-borne disease risk is imperative to them [46, 47]. Student-led households were more likely to observe the safe water chain as compared to those who were engaged with business. This finding was understandable as students are likely to be routinely taught WASH aspects at school. Indeed, some studies have demonstrated that students can learn many things at school and influence behavior change in their homes and communities [48, 49]. This shows that education can influence household practices on safe water chain. Household heads who had attained post-primary education were more likely to observe safe water chain compared to those with primary or no education. This finding is in line with studies [50, 51, 52] which indicated that high levels of education result in adoption of better decisions on safe water management. Educational awareness programs on safe water chain are needed to benefit individuals with low education status and consequently minimize risk due to poor safe water practices.

Contamination of water can occur at any point in the water chain from the source to the point of use [53, 54]. In our study, household heads who thought most contamination occurs during storage were more likely to observe safe water chain compared to those who thought it occurs more at the source. It is known that significant recontamination of water can occur through drawing it with cups and hands as reported in other studies [55, 56]. Evidence also shows that point-of-source bacterial contamination may be rare when water is obtained from standpipes or taps as in the case of this setting. In fact, many city water supplies are treated centrally in conventional systems but contamination could occur mostly through unsafe water storage [57, 58]. However, there is a need to educate slum dwellers on critical safe water chain practices that need to be maintained along the entire drinking water chain as demonstrated in an Ethiopian study on the effect of WASH on childhood illnesses [59].

Our study is limited by the fact that all practices reported about were self-reported and could have been subject to social desirability bias. However, the study makes a significant contribution regarding safe water chain maintenance in an urban slum which has rarely been researched. The study findings could also be generalizable to other slums in Kampala city as these have been reported to be similar in context.

Conclusion

Knowledge on the safe water chain was generally satisfactory although only a third of the households maintained the safe water chain. Female-headed households, post-primary educated household heads, and student-led households were significantly more likely to maintain the safe water chain. Therefore, there is a need to improve safe water chain practices among slum household through continuous health education on the importance of using and drinking safe water.

Notes

Acknowledgements

We would like to thank the Stanbic Bank Uganda Limited for supporting this study. Our appreciation goes to the Environmental Health Science students of Makerere University who collected the data for their time and commitment during the course of the research. Special thanks go to the community health workers and local leaders for their support offered during data collection.

Authors’ contributions

CS, DM, JO, and AAH conceptualized the study and were involved in the data collection, analysis, and manuscript writing. STW, FO, and RN were involved in the data collection, analysis, and manuscript writing. All authors read and approved the final manuscript.

Funding

This study was supported by Stanbic Bank, Uganda Limited. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of Stanbic Bank, Uganda Limited.

Ethics approval and consent to participate

The study was approved by Makerere University School of Public Health Higher Degrees, Research, and Ethics Committee. All participants provided written informed consent before their involvement in the study.

Consent for publication

All study participants provided written consent for their data to be used in reports and publications.

Competing interests

The authors declare that they have no competing interests.

References

  1. 1.
    Rosen S, Vincent JR. Household water resources and rural productivity in sub-Saharan Africa: a review of the evidence; 2001.Google Scholar
  2. 2.
    Prüss-Ustün A, Bartram J, Clasen T, Colford JM, Cumming O, Curtis V, et al. Burden of disease from inadequate water, sanitation and hygiene in low-and middle-income settings: a retrospective analysis of data from 145 countries. Tropical Med Int Health. 2014;19(8):894–905.CrossRefGoogle Scholar
  3. 3.
    Cairncross S, Hunt C, Boisson S, Bostoen K, Curtis V, Fung IC, et al. Water, sanitation and hygiene for the prevention of diarrhoea. Int J Epidemiol. 2010;39(suppl 1):i193–205.CrossRefGoogle Scholar
  4. 4.
    Esrey SA, Potash JB, Roberts L, Shiff C. Effects of improved water supply and sanitation on ascariasis, diarrhoea, dracunculiasis, hookworm infection, schistosomiasis, and trachoma. Bull World Health Organ. 1991;69(5):609.PubMedPubMedCentralGoogle Scholar
  5. 5.
    World Health Organization, WHO/UNICEF Joint Water Supply. Sanitation monitoring programme. In: Progress on sanitation and drinking water: 2015 update and MDG assessment: World Health Organization; 2015.Google Scholar
  6. 6.
    Hogrewe W, Joyce SD, Perez EA. Unique challenges of improving peri-urban sanitation: US Agency for International Development Washington (DC); 1993.Google Scholar
  7. 7.
    Bwire G, Malimbo M, Maskery B, Kim YE, Mogasale V, Levin A. The burden of cholera in Uganda. PLoS Negl Trop Dis. 2013;7(12):e2545.CrossRefGoogle Scholar
  8. 8.
    World Health Organization. Typhoid fever – Uganda. World Health Organization; 2015. Contract no.: 22nd March 2016.Google Scholar
  9. 9.
    Kimani-Murage EW, Ngindu AM. Quality of water the slum dwellers use: the case of a Kenyan slum. J Urban Health. 2007;84(6):829–38.CrossRefGoogle Scholar
  10. 10.
    Haruna R, Ejobi F, Kabagambe EK. The quality of water from protected springs in Katwe and Kisenyi parishes, Kampala city, Uganda. Afr Health Sci. 2005;5(1):14–20.PubMedPubMedCentralGoogle Scholar
  11. 11.
    Musoke D, Ndejjo R, Halage AA, Kasasa S, Ssempebwa JC, Carpenter DO. Drinking water supply, sanitation, and hygiene promotion interventions in two slum communities in Central Uganda. J Environ Public Health. 2018;2018:1–9.CrossRefGoogle Scholar
  12. 12.
    Fewtrell L, Kaufmann RB, Kay D, Enanoria W, Haller L, Colford JM. Water, sanitation, and hygiene interventions to reduce diarrhoea in less developed countries: a systematic review and meta-analysis. Lancet Infect Dis. 2005;5(1):42–52.CrossRefGoogle Scholar
  13. 13.
    Clasen TF, Cairncross S. Household water management: refining the dominant paradigm. Tropical Med Int Health. 2004;9(2):187–91.CrossRefGoogle Scholar
  14. 14.
    Mukama T, Ndejjo R, Musoke D, Musinguzi G, Halage AA, Carpenter DO, et al. Practices, concerns and willingness to participate in solid waste management in two urban slums in central Uganda. J Environ Public Health. 2016.Google Scholar
  15. 15.
    United Nations. Millennium development goals indicators: the official United Nations site for MDGs indicators Nairobi. Kenya: UN-Habitat; 2014. Available from: http://mdgs.un.org/unsd/mdg/Metadata.aspx?IndicatorId=32 Google Scholar
  16. 16.
    Tumwebaze IK, Lüthi C. Households’ access and use of water and sanitation facilities in poor urban areas of Kampala, Uganda. J Water Sanitation Hyg Dev. 2013;3(2):96–105.CrossRefGoogle Scholar
  17. 17.
    Kabwama SN, Bulage L, Nsubuga F, Pande G, Oguttu DW, Mafigiri R, et al. A large and persistent outbreak of typhoid fever caused by consuming contaminated water and street-vended beverages: Kampala, Uganda, January – June 2015. BMC Public Health. 2017;17(1):23.Google Scholar
  18. 18.
    Dimanin P. Exploring livelihoods of the urban poor in Kampala, Uganda: an institutional, community, and household contextual analysis. Kampala: ACF Internarional; 2012.Google Scholar
  19. 19.
    Nolan LB. Slum definitions in urban India: implications for the measurement of health inequalities. Popul Dev Rev. 2015;41(1):59–84.CrossRefGoogle Scholar
  20. 20.
    UBOS. National population and housing census 2014 provisional results Kampala Uganda Bureau of Statistics 2014.Google Scholar
  21. 21.
    Wiegand H. Kish, L.: Survey Sampling. John Wiley & Sons, Inc., New York, London 1965, IX + 643 S., 31 Abb., 56 Tab., Preis 83 s. Biom Z 1968;10(1):88–89.Google Scholar
  22. 22.
    Daniel WW, Cross CL. Biostatistics: a foundation for analysis in the health sciences. 10th ed. New York: John Wiley and Sons; 1999.Google Scholar
  23. 23.
    Lwanga SK, Lemeshow S. Sample size determination in health studies : a practical manual. Geneva: World Health Organisation; 1991.Google Scholar
  24. 24.
    Macfarlane SB. Conducting a descriptive survey: 2. Choosing a sampling strategy. Trop Dr. 1997;27(1):14–21.Google Scholar
  25. 25.
    UBOS. Compendium of statistical concepts and definitions used in the Uganda statistical system and services Kampala: Uganda Bureau of Statistics 2001.Google Scholar
  26. 26.
    Inauen J, Mosler H-J. Mechanisms of behavioural maintenance: long-term effects of theory-based interventions to promote safe water consumption. Psychol Health. 2016;31(2):166–83.CrossRefGoogle Scholar
  27. 27.
    Cengage Learning I. Carrying out the work operation and maintenance of water supply distribution network by providing clean and safe supply of water at ward no. 20,21,33,34,35,36,37,38,39,40,42 & Wtp at Shorgumbaz area in South Assembly Areas of Kalburgi City by engaging Req. SyndiGate Media Inc.; 2016.Google Scholar
  28. 28.
    Grant P. Mixing valves deliver safe water temperatures proper equipment maintenance is the key to safeguarding against injuries. Reeves Journal. 2005;85(8):70.Google Scholar
  29. 29.
    ProQuest LLC. Supplying, fitting, fixing, installation execution and maintenance (two year) of safe purified R.o. based community drinking water system [Tender documents: T37959500]. London: Albawaba (London) Ltd; 2017.Google Scholar
  30. 30.
    Misati A. Household safe water management in Kisii County, Kenya. Environ Health Prev Med. 2016;21(6):450–4.CrossRefGoogle Scholar
  31. 31.
    Pendić Z, Polak-Pendić S, Jakovljević B, Strižak M, Lačnjevac Č, Vujotić L, et al. Analysis of application of different approaches to secure safe drinking water. Tehnika. 2017;72(1):147–55.CrossRefGoogle Scholar
  32. 32.
    Andrade C. Understanding relative risk, odds ratio, and related terms: as simple as it can get. J Clin Psychiatry. 2015;76(7):e857–61.CrossRefGoogle Scholar
  33. 33.
    Schmidt CO, Kohlmann T. When to use the odds ratio or the relative risk? Int J Public Health. 2008;53(3):165–7.CrossRefGoogle Scholar
  34. 34.
    Boadi KOKM. Environmental and health impacts of household solid waste handling and disposal practices in third world cities: the case of the Accra Metropolitan Area, Ghana. J Environ Health. 2005;68(4):32–6.PubMedGoogle Scholar
  35. 35.
    Satapathy BK. Safe drinking water in slums; from water coverage to water quality economic and political weekly special article, vol. 44; 2014. p. 24.Google Scholar
  36. 36.
    WHO/UNICEF. Coverage estimates: improved drinking water—Uganda. In: WHO/UNICEF joint monitoring programme for water supply and sanitation; 2006. [Available from: https://washdata.org/monitoring/drinking-water.
  37. 37.
    Murphy JL, Kahler AM, Nansubuga I, Nanyunja EM, Kaplan B, Jothikumar N, et al. Environmental survey of drinking water sources in Kampala, Uganda, during a typhoid fever outbreak. Appl Environ Microbiol. 2017;83(23)1–11.Google Scholar
  38. 38.
    WHO. Typhoid fever - Uganda. Geneva: World Health Organisation; 2015.Google Scholar
  39. 39.
    Verma R, Singh A, Khurana A, Dixit P, Singh R. Practices and attitudinal behavior about drinking water in an urban slum of district Rohtak, Haryana: a community-based study. J Fam Med Prim Care. 2017;6(3):554–7.CrossRefGoogle Scholar
  40. 40.
    Bukenya JO. Avoidance measures and household perceptions of water quality in Uganda. J Afr Bus. 2008;9(2):309–25.CrossRefGoogle Scholar
  41. 41.
    Rosa G, Clasen T. Estimating the scope of household water treatment in low- and medium-income countries. Am J Trop Med Hyg. 2010;82(2):289–300.CrossRefGoogle Scholar
  42. 42.
    Sobsey MD. Managing water in the home: accelerated health gains from improved water supply. Geneva: World Health Organization; 2002.Google Scholar
  43. 43.
    Fotuè LAT. Awareness and the demand for improved drinking water source in Cameroon. Int J Econ Prac Theor. 2013;3(1):50–9.Google Scholar
  44. 44.
    WHO. Water safety planning for small water supplies 2012 Available from: http://www.who.int/iris/handle/10665/75145.
  45. 45.
    NWDR. Uganda national water development report 2005 Available from: http://unesdoc.unesco.org/images/0014/001467/146760e.pdf.Google Scholar
  46. 46.
    Abebaw D, Tadesse F, Mogues T. Access to improved water source and satisfaction with services. Evidence from rural Ethiopia: the international food policy research institute; 2011.Google Scholar
  47. 47.
    Caruso BA, Sevilimedu V, Fung IC-H, Patkar A, Baker KK. Gender disparities in water, sanitation, and global health. Lancet. 2015;386(9994):650–1.CrossRefGoogle Scholar
  48. 48.
    Onyango-Ouma W, Aagaard-Hansen J, Jensen BB. The potential of school children as health change agents in rural western Kenya. Soc Sci Med. 2005;61:1711–22.CrossRefGoogle Scholar
  49. 49.
    O'Reilly CE, Freeman MC, Ravani M, et al. The impact of a school based safe water and hygiene programme on knowledge and practices of students and their parents: Nyanza province Western Kenya. Epidemiol Infect. 2006;136:80–91.CrossRefGoogle Scholar
  50. 50.
    Totouom A, Fouéka Tagne SR, Ngouhouo Poufoun J. Determinants of the avoidance behaviour of households to cope with unsafe drinking water: case study of Douala and Yaoundé in Cameroon. Rev Agric Food Environ Stud. 2018;99(2):1–28.CrossRefGoogle Scholar
  51. 51.
    Freeman MC, Trinies V, Boisson S, Mak G, Clasen T. Promoting household water treatment through women’s self help groups in rural India: assessing impact on drinking water quality and equity. PLoS One. 2012;7(9):e44068.CrossRefGoogle Scholar
  52. 52.
    Geremew A, Mengistie B, Mellor J, Lantagne DS, Alemayehu E, Sahilu GJEH, et al. Appropriate household water treatment methods in Ethiopia: household use and associated factors based on 2005, 2011, and 2016 EDHS data. Environ Health Prev Med. 2018;23(1):46.Google Scholar
  53. 53.
    Wright J, Gundry S, Conroy R. Household drinking water in developing countries: a systematic review of microbiological contamination between source and point-of-use. Tropical Med Int Health. 2004;9(1):106–17.CrossRefGoogle Scholar
  54. 54.
    Clasen TF, Bastable A. Faecal contamination of drinking water during collection and household storage: the need to extend protection to the point of use. J Water Health Place. 2003;1(3):109–15.CrossRefGoogle Scholar
  55. 55.
    VanDerslice J, Briscoe J. All coliforms are not created equal: a comparison of the effects of water source and in-house water contamination on infantile diarrheal disease. J Water Resour Res. 1993;29(7):1983–95.CrossRefGoogle Scholar
  56. 56.
    Gundry SW, Wright JA, Conroy R, Du Preez M, Genthe B, Moyo S, et al. Contamination of drinking water between source and point-of-use in rural households of South Africa and Zimbabwe: implications for monitoring the Millennium Development Goal for water. J Water Prac Tech. 2006;1(2):wpt2006032.Google Scholar
  57. 57.
    Oswald WE, Lescano AG, Bern C, Calderon MM, Cabrera L, Gilman RH. Fecal contamination of drinking water within peri-urban households, Lima, Peru. Am J Trop Med Hyg. 2007;77(4):699–704.CrossRefGoogle Scholar
  58. 58.
    Subbaraman R, Shitole S, Shitole T, Sawant K, O’brien J, Bloom DE, et al. The social ecology of water in a Mumbai slum: failures in water quality, quantity, and reliability. BMC Public Health. 2013;13(1):173.CrossRefGoogle Scholar
  59. 59.
    Gizaw Z, Addisu A, Dagne HJEH, Medicine P. Effects of water, sanitation and hygiene (WASH) education on childhood intestinal parasitic infections in rural Dembiya, northwest Ethiopia: an uncontrolled before-and-after intervention study. Environ Health Prev Med. 2019;24(1):16.Google Scholar

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Authors and Affiliations

  1. 1.Department of Disease Control and Environmental Health, School of Public HealthMakerere University College of Health SciencesKampalaUganda

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