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The health impact of sanitation

The health impact of sanitation. Sandy Cairncross Professor of Environmental Health London School of Hygiene & Tropical Medicine sandy.cairncross@lshtm.ac.uk. Health may be a major benefit, but it is not the main one in the eyes of the consumer.

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The health impact of sanitation

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  1. The health impact of sanitation Sandy Cairncross Professor of Environmental Health London School of Hygiene & Tropical Medicine sandy.cairncross@lshtm.ac.uk

  2. Health may be a major benefit, but it is not the main one in the eyes of the consumer.

  3. Benefits of latrine to 320 households in rural Benin (Average importance rating, scale 1-4) Avoid discomforts of the bush 3.98 Gain prestige from visitors 3.96 Avoid dangers at night 3.86 Avoid snakes 3.85 Reduce flies in compound 3.81 Avoid risk of smelling/seeing faeces in bush 3.78 Protect my faeces from enemies 3.71 Have more privacy to defecate 3.67 Keep my house/property clean 3.59 Feel safer 3.56 Save time 3.53 Make my house more comfortable 3.50 Reduce my household’s health care expenses 3.32 Leave a legacy for my children 3.16 Have more privacy for household affairs 3.00 Make my life more modern 2.97 Feel royal 2.75 Make it easier to defecate due to age/sickness 2.62 Be able to increase my tenants’ rent 1.17 For health (spontaneous mention) 1.27 Source: Jenkins MW (1999) PhD thesis, UC Davis, Civil Engineering

  4. Fewtrell et al. (2004) review: “No study excluded on basis of quality alone” Criteria for “good” studies: • Adequate control group • Clear measurement/control of confounders • Diarrhoea outcome defined • Recall period ≤ 2 weeks NB Observational studies included

  5. Previous reviews: a – d Esrey SA et al. (1991) Bull WHO 69 (5): 609-621 e Curtis V, Cairncross S (2003) Lancet Inf Dis 3: 275-281.

  6. Problems with systematic reviews: • Confounding in observational studies • No placebo in intervention studies • Trade-off between quality and numbers • Wide confidence intervals • Who defines quality? “Judgement-free data” are a mirage • Extrapolation from morbidity to mortality • Publication bias • Bottom-line impact figure obscures variation

  7. Health impact measurement; a cautionary tale

  8. Health impact measurement; a cautionary tale Village Piped water Dug hole Namabengo 15/216 ( 7%) Mkongo 39/134 (29%) Children < 5 years with diarrhoea during previous week Source: Prag JB et al. (1983) Water Master Plan for Iringa, Ruvuma and Mbeya Regions, Tanzania Vol. 13 Ch. 11.

  9. Health impact measurement; a cautionary tale Village Piped water Dug hole Namabengo 15/216 ( 7%) Mkongo 39/134 (29%) Children < 5 years with diarrhoea during previous week Village Piped water Dug hole Namabengo 4/216 (1.9%) Mkongo 12/133 (9.0%) Children < 5 years with positive Widal (S. typhi H antigen) Source: Prag JB et al. (1983) Water Master Plan for Iringa, Ruvuma and Mbeya Regions, Tanzania Vol. 13 Ch. 11.

  10. Health impact measurement; a cautionary tale Village Piped water Dug hole Namabengo 15/216 ( 7%) 5/70 ( 7%) Mkongo 37/100 (37%) 39/134 (29%) Children < 5 years with diarrhoea during previous week Village Piped water Dug hole Namabengo 4/216 (1.9%) 1/70 (1.4%) Mkongo 7/100 (7.0%) 12/133 (9.0%) Children < 5 years with positive Widal (S. typhi H antigen) Source: Prag JB et al. (1983) Water Master Plan for Iringa, Ruvuma and Mbeya Regions, Tanzania Vol. 13 Ch. 11.

  11. Namabengo: Higher altitude, cooler, less growth of faecal pathogens Large mission hospital, handing out antimalarials - and malaria causes immunosuppression Away from the lake area, affected by a typhoid outbreak

  12. Health impact measurement; a cautionary tale Village Piped water Dug hole Namabengo 15/216 ( 7%) 5/70 ( 7%) Mkongo 37/100 (37%) 39/134 (29%) Totals 52/316 (16%) 44/204 (22%) Children < 5 years with diarrhoea during previous week Village Piped water Dug hole Namabengo 4/216 (1.9%) 1/70 (1.4%) Mkongo 7/100 (7.0%) 12/133 (9.0%) Totals 11/316 (3.5%) 13/203 (6.4%) Children < 5 years with positive Widal (S. typhi H antigen) Source: Prag JB et al. (1983) Water Master Plan for Iringa, Ruvuma and Mbeya Regions, Tanzania Vol. 13 Ch. 11.

  13. Multivariate analysis is not guaranteed to remove confounding, especially when RR < 2

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  16. ‘Determinants’ of good hand washing among 90 rural Bangladeshi women Observed hand washing behaviour after defecation Good Poor Rel. rate (95% CI) Own sanitary latrine used yes 22 11 1.73 (1.15-2.59) no 22 35 Owns agricultural land yes 36 24 2.25 (1.20-4.22) no 8 22 Believes that washing hands prevents diseases yes 26 27 1.01 (0.66-1.55) no 21 18 Source: Hoque BA et al. (1995) Public Health 109: 15-24

  17. Can television protect you from diarrhoea?

  18. “Long-term longitudinal studies of large size and expense are probably the only means through which there is any chance of isolating a specific quantitative relationship between water supply and health… [Given] the very high cost, limited possibility of success and restricted application of results, [such studies should not be undertaken].” Source: World Bank (1976) Measurement of the health benefits of investments in water supply. Report of an Expert Panel, Public Utilities Dept. Report no. PUN 20.

  19. Conclusion: • Measuring health benefits is tricky; better to measure intermediate variables • access • time saving, cost reduction • hygiene

  20. Most sanitation health impact studies: • are observational • (hence subject to confounding) • But also • are in rural settings • don’t allow for “mass effect” • have a single disease outcome

  21. Excreta-related infections After Feachem et al. (1983)

  22. Risk factors for infection with Giardia in Salvador, Brazil Source: Prado et al. (2003) Epidemiol. Infect. 131(2): 899-906

  23. Fly control in Gambia Period prevalence of diarrhoea (%) Wet season Dry season Intervention village 14 6 Control village 19 8 Relative risk 0.78 0.74 Mean reduction in diarrhoea prevalence 24% (Mean reduction in trachoma incidence 75%!) Source: Emerson PM et al. (1999) Lancet353: 1401-1403

  24. Drainage and ascariasis in Salvador, Brazil ___________ ________ Without drains With drains Prevalence of infection (%) 66.4 47.1 Significance of household clustering NS * No. of significant household risk factors Relative risk of reinfection (9 months) (95% Confidence Interval) Correlation of infection/reinfection egg counts (Pearson's r; N = no. of children infected twice) Significance of correlation _______________________________________________________________________ * p < 0.001

  25. Drainage and ascariasis in Salvador, Brazil ___________ ________ Without drains With drains Prevalence of infection (%) 66.4 47.1 Significance of household clustering NS * No. of significant household risk factors 5 9 Relative risk of reinfection (9 months) (95% Confidence Interval) Correlation of infection/reinfection egg counts (Pearson's r; N = no. of children infected twice) Significance of correlation _______________________________________________________________________ * p < 0.001

  26. Drainage and ascariasis in Salvador, Brazil ___________ ________ Without drains With drains Prevalence of infection (%) 66.4 47.1 Significance of household clustering NS * No. of significant household risk factors 5 9 Relative risk of reinfection (9 months) 1.30 2.35 (95% Confidence Interval) (1.12-1.52) (1.93-2.86) Correlation of infection/reinfection egg counts (Pearson's r; N = no. of children infected twice) Significance of correlation _______________________________________________________________________ * p < 0.001

  27. Drainage and ascariasis in Salvador, Brazil ___________ ________ Without drains With drains Prevalence of infection (%) 66.4 47.1 Significance of household clustering NS * No. of significant household risk factors 5 9 Relative risk of reinfection (9 months) 1.30 2.35 (95% Confidence Interval) (1.12-1.52) (1.93-2.86) Correlation of infection/reinfection egg counts 0.05 0.23 (Pearson's r; N = no. of children infected twice) (N=250) (N=166) Significance of correlation NS * _______________________________________________________________________ * p < 0.001

  28. Public domain transmission: Externalities apply Control requires public action: - investment in infrastructure,or - regulation (by-laws, quality standards)

  29. Public domain transmission: Externalities apply Control requires public action: - investment in infrastructure,or - regulation (by-laws, quality standards) Domestic domain transmission: A question of hygiene behaviour Control requires health promotion - but infrastructure may also be necessary

  30. Public and domestic domains Peri-domestic Home (street, school, work-place) River & Environs City Ward

  31. Secondary Distribution Network Primary Distribution Network River & Environs City Transmission Line, and Storage Ward Peri-domestic Home House Connection Water Treatment Plant (street, school, work-place) Raw water intake

  32. Home Peri-domestic (street,school, workplace) Ward City Central Treatment Works Primary Mains Street Mains House Connections

  33. Brown vs. Green agenda “The problems of the poor are suffered by the poor and dealt with by the poor” Marianne Kjellen

  34. Brown vs. Green agenda “The problems of the poor are suffered by the poor and dealt with by the poor; The problems of the rich are suffered by the public and dealt with by the Government” Marianne Kjellen

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