Volume 97, Issue 5
  • ISSN: 0002-9637
  • E-ISSN: 1476-1645



Water-related diseases are closely linked with drinking water, sanitation, and hygiene (WASH) indicators, socioeconomic status, education level, or dwelling’s conditions. Developing countries exhibit a particular vulnerability to these diseases, especially rural areas and urban slums. This study assessed socioeconomic features, WASH indicators, and water-related diseases in two rural areas of the Colombian Caribbean coast. Most of this population did not finish basic education (72.3%, = 159). Only one of the communities had a water supply (aqueduct), whereas the other received water via an adapted tanker ship. No respondents reported sewage services; 92.7% ( = 204) had garbage service. Reported cases of diarrhea were associated with low education levels ( = 2.37 × 10) and an unimproved drinking water supply ( = 0.035). At least one fever episode was reported in 20% ( = 44) of dwellings, but the cases were not related to any indicator. The House index (percentage of houses that tested positive for larvae and/or pupae) was 69%, the container index (percentage of water-holding containers positive for larvae or pupae) 29.4%, and the Breteau index (number of positive containers per 100 houses in a specific location) was three positive containers per 100 inspected houses. The presence of positive containers was associated with the absence of a drinking water supply ( = 0.04). The community with poorer health indicators showed greater health vulnerability conditions for acquisition of water-related diseases. In summary, water supply and educational level were the main factors associated with the presence of water-related diseases in both communities.


Article metrics loading...

The graphs shown below represent data from March 2017
Loading full text...

Full text loading...



  1. Mor SM, Griffiths JK, 2011. Water-related diseases in the developing world. Nriagu JO, ed. Encyclopedia of Environmental Health. Burlington, MA: Elsevier, 741753.
  2. Griffiths JK, 2008. Waterborne diseases. Heggenhougen HK, ed. International Encyclopedia of Public Health. Oxford, United Kingdom: Academic Press, 551563.
  3. Epstein PR, 2001. Climate change and emerging infectious diseases. Microbes Infect 3: 747754.[Crossref]
    [Google Scholar]
  4. World Health Organization, UNICEF, 2015. Progress on Sanitation and Drinking-Water: 2015 Update and MDG Assessment. Geneva, Switzerland: World Health Organization.
  5. Prüss-Üstün A et al., 2014. Burden of disease from inadequate water, sanitation and hygiene in low- and middle-income settings: a retrospective analysis of data from 145 countries. Trop Med Int Health 19: 894905.[Crossref]
    [Google Scholar]
  6. World Health Organization, UNICEF, 2015. Progress on Sanitation and Drinking-Water: 2014 Update and MDG Assessment. Geneva, Switzerland: World Health Organization.
  7. Griffiths JK, 2017. Waterborne diseases. Quah SR, ed. International Encyclopedia of Public Health, 2nd edition. Oxford, United Kingdom: Academic Press, 388401.
  8. Polwiang S, 2015. The seasonal reproduction number of dengue fever: impacts of climate on transmission. PeerJ 3: e1069.[Crossref]
    [Google Scholar]
  9. MacLeod DA, Morse AP, 2014. Visualizing the uncertainty in the relationship between seasonal average climate and malaria risk. Sci Rep 4: 7264.[Crossref]
    [Google Scholar]
  10. IPCC, 2014. Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, United Kingdom: Cambridge University Press.
  11. Koskei EC, Koskei RC, Koske MC, Koech HK, 2013. Effect of socio-economic factors on access to improved water sources and basic sanitation in Bomet Municipality, Kenya. Res J Environ Earth Sci 5: 714719.
    [Google Scholar]
  12. Prüss-Üstün A, Bos R, Gore F, Bartram J, 2008. Safer Water, Better Health: Costs, Benefits and Sustaninability of Interventions to Protect and Promote Health. Geneva, Switzerland: World Health Organization.
  13. Smith KR, Woodward A, Campbell-Lendrum D, Chadee DD, Honda Y, Liu Q, Olwoch JM, Revich B, Sauerborn R, 2014. Human health: impacts, adaptation, and co-benefits. Field CB, et al., eds. Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel of Climate Change. Cambridge, United Kingdom: Cambridge University Press, 709754.
  14. Departamento Administrativo Distrital de Salud, 2012. Perfil Epidemiológico de Cartagena de Indias. Cartagena de Indias: Alcaldía de Cartagena de Indias.
  15. Departamento Administrativo Nacional de Estadística, 2006. Censo General de 2005: nivel nacional. Bogotá, Colombia: Departamento Administrativo Nacional de Estadística.
  16. Mejia G, Ramos-Clason E, Mazenett E, Morelos J, Malambo D, Maestre R, Mora-Garcia G, Gomez D, 2010. Estimate of risk factors for leptospirosis in Cartagena de Indias-Colombia. Am J Trop Med Hyg 83: 308s309s.
    [Google Scholar]
  17. Alcaldía de Cartagena de Indias, 2016. Cartagena Info. Available at: http://cartagenainfo.cartagena.gov.co:83/libraries/aspx/home.aspx. Accessed February 16, 2016.
  18. Gambino JG, 2012. Functions for PPS sampling. R package version 0.94. Available at: https://CRAN.R-project.org/package=pps. Accessed March 15, 2014.
  19. Brogan D, Flagg EW, Deming M, Waldman R, 1994. Increasing the accuracy of the expanded programme on immunization’s cluster survey design. Ann Epidemiol 4: 302311.[Crossref]
    [Google Scholar]
  20. Manzur F, Alvear C, Alayón A, 2009. El perfil epidemiológico del sobrepeso y la obesidad y sus principales comorbilidades en la ciudad de Cartagena de Indias. Revista Colombiana de Cardiología 16: 194200.
    [Google Scholar]
  21. Mora Garcia G, Salguedo Madrid G, Ruiz Diaz M, Ramos Clason E, Alario Bello A, Fortich A, Mazenett E, Gomez Camargo D, Gomez Alegria C, 2012. Agreement between five definitions of metabolic syndrome: Cartagena, Colombia. Rev Esp Salud Publica 86: 301311.[Crossref]
    [Google Scholar]
  22. Ministerio de Desarrollo Social, 2013. Libro de códigos base de datos Encuesta de Caracterización Socioeconómica Nacional CASEN 2013. Serie Documentos Metodológicos No. 31. Available at: http://www.ministeriodesarrollosocial.gob.cl/. Accessed July 6, 2017.
  23. Bunster V, Noguchi M, 2015. Profiling space heating behavior in Chilean social housing: towards personalization of energy efficiency measures. Sustainability 7: 79737996.[Crossref]
    [Google Scholar]
  24. WHO/UNICEF Joint Monitoring Programme for Water Supply and Sanitation, 2008. Progress on Drinking-Water and Sanitation: Special Focus on Sanitation. Geneva, Switzerland: World Health Organization.
  25. Mejia G, Mora G, Ramos E, Maestre R, Mazenett E, Malambo D, Gomez D, 2011. Identificacion Genetica de Subpoblaciones de Aedes aegypti en Cartagena de Indias, Colombia. Rev Cinc Biomed 2: 1s.
    [Google Scholar]
  26. World Health Organization, Regional Office for the Western Pacific, 2003. Guidelines for Dengue Surveillance and Mosquito Control. Manila: WHO Regional Office for the Western Pacific.
  27. World Health Organization, 2009. Dengue Guidelines for Diagnosis, Treatment, Prevention and Control: New Edition. Geneva, Switzerland: World Health Organization.
  28. R Core Team, 2016. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. Available at: http://www.r-project.org/. Accessed January 19, 2016.
  29. Liaw A, Wiener M, 2002. Classification and regression by random forest. R News 2: 1822.
    [Google Scholar]
  30. Lunetta KL, Hayward LB, Segal J, Van Eerdewegh P, 2004. Screening large-scale association study data: exploiting interactions using random forests. BMC Genet 5: 32.[Crossref]
    [Google Scholar]
  31. Muttarak R, Lutz W, 2014. Is education a key to reducing vulnerability to natural disasters and hence unavoidable climate change? Ecol Soc 19: 42.[Crossref]
    [Google Scholar]
  32. Zamora-Bornachera A, Narváez-Barandica J, Londoño-Díaz L, 2007. Evaluación económica dela pesquería artesanal de la Ciénaga Grande de Santa Marta y Complejo de Pajarales, Caribe Colombiano. Bol Investig Mar Costeras 36: 3348.
    [Google Scholar]
  33. Aguilera Diaz M, 2006. El Canal del Dique y su subregión: Una economía basada en la riqueza hídrica. Cartagena de Indias.
  34. Ninphanomchai S, Chansang C, Hii YL, Rocklov J, Kittayapong P, 2014. Predictiveness of disease risk in a global outreach tourist setting in Thailand using meteorological data and vector-borne disease incidences. Int J Environ Res Public Health 11: 1069410709.[Crossref]
    [Google Scholar]
  35. Barnighausen T, Bloom DE, Cafiero ET, O’Brien JC, 2013. Valuing the broader benefits of dengue vaccination, with a preliminary application to Brazil. Semin Immunol 25: 104113.[Crossref]
    [Google Scholar]
  36. Ministerio de Planificación de la República de Chile, 2006. Encuesta de Caracterización Socioeconómica Nacional. Santiago de Chile.
  37. Mosquera PA, Hernandez J, Vega R, Martinez J, Labonte R, Sanders D, San Sebastian M, 2012. Primary health care contribution to improve health outcomes in Bogota-Colombia: a longitudinal ecological analysis. BMC Fam Pract 13: 84.[Crossref]
    [Google Scholar]
  38. Salinas Ramírez J, 2011. Retos a futuro en el sector de acueducto y alcantarillado en Colombia. Colección de Documentos de Proyectos. Santiago de Chile.
  39. Oakley SM, Jimenez R, 2012. Sustainable sanitary landfills for neglected small cities in developing countries: the semi-mechanized trench method from Villanueva, Honduras. Waste Manag 32: 25352551.[Crossref]
    [Google Scholar]
  40. Rego RF, Moraes LRS, Dourado I, 2005. Diarrhoea and garbage disposal in Salvador, Brazil. Trans R Soc Trop Med Hyg 99: 4854.[Crossref]
    [Google Scholar]
  41. Koola J, Zwane AP, 2014. Water supply and sanitation. Culyer AJ, ed. Encyclopedia of Health Economics. San Diego, CA: Elsevier, 477482.
  42. Diouf K, Tabatabai P, Rudolph J, Marx M, 2014. Diarrhoea prevalence in children under five years of age in rural Burundi: an assessment of social and behavioural factors at the household level. 7: 24895.
  43. Shah SM, Yousafzai M, Lakhani NB, Chotani RA, Nowshad G, 2003. Prevalence and correlates of diarrhea. Indian J Pediatr 70: 207211.[Crossref]
    [Google Scholar]
  44. Brick T, Primrose B, Chandrasekhar R, Roy S, Muliyil J, Kang G, 2004. Water contamination in urban south India: household storage practices and their implications for water safety and enteric infections. Int J Hyg Environ Health 207: 473480.[Crossref]
    [Google Scholar]
  45. Clark R, 2013. Drinking Water Distribution Systems: Their Role in Reducing Risks and Protecting Public Health. Reference Module in Earth Systems and Environmental Sciences. Available at: http://www.sciencedirect.com/science/article/pii/B9780124095489022387. Accessed January 24, 2017.
  46. World Health Organization, 2014. UN-Water Global Analysis and Assessment of Sanitation and Drinking-Water (GLAAS) 2014 Report: Investing in Water and Sanitation: Increasing Access, Reducing Inequalities. Geneva, Switzerland: World Health Organization.
  47. Guzmán Barrangán B, Nava Tovar G, 2015. Estado de la Vigilancia de la calidad de agua para consumo Humano–2014. Bogota, Colombia: Instituto Nacional de Salud.
  48. Barrera R, Avila J, Gonzalez-Tellez S, 1993. Unreliable supply of potable water and elevated Aedes aegypti larval indices: a causal relationship? J Am Mosq Control Assoc 9: 189195.
    [Google Scholar]
  49. Barrera R, Navarro JC, Mora JD, Dominguez D, Gonzalez J, 1995. Public service deficiencies and Aedes aegypti breeding sites in Venezuela. Bull Pan Am Health Organ 29: 193205.
    [Google Scholar]
  50. Chadee DD, Rahaman A, 2000. Use of water drums by humans and Aedes aegypti in Trinidad. J Vector Ecol 25: 2835.
    [Google Scholar]
  51. Fuentes-Vallejo M, Higuera-Mendieta DR, Garcia-Betancourt T, Alcala-Espinosa LA, Garcia-Sanchez D, Munevar-Cagigas DA, Brochero HL, Gonzalez-Uribe C, Quintero J, 2015. Territorial analysis of Aedes aegypti distribution in two Colombian cities: a chorematic and ecosystem approach. Cad Saude Publica 31: 517530.[Crossref]
    [Google Scholar]
  52. Alcala L, Quintero J, Gonzalez-Uribe C, Brochero H, 2015. Estimation of Aedes aegypti (L.) (Diptera: Culicidae) productivity in households and public spaces in a dengue endemic city in Colombia. Biomedica 35: 258268.[Crossref]
    [Google Scholar]

Data & Media loading...

  • Received : 18 Apr 2016
  • Accepted : 09 Aug 2017
  • Published online : 25 Sep 2017
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error