Advertisement

Importance of Appropriate and Reliable Population Data in Developing Regions to Understand Epidemiology of Diseases

  • Satoshi KanekoEmail author
  • Morris Ndemwa
Chapter

Abstract

Many developing countries lack a reliable resident registration system, resulting in difficult challenges in understanding health status of a population. Attempts have been made to establish an efficient system in developing countries, particularly in rural areas. WHO reported that only five African countries had vital registration systems covering more than 25% of their population. Such attempts made to bridge the gap include verbal autopsy tools within the HDSS program, the tools to capture causes of death guided by WHO principles of determining causes of death, where elaborated systems for defining causes of deaths do not exist. In addition, observational and interventional studies can be conducted within an established HDSS platform. The idea of HDSS originated from the concept of a prospective community study (PCS), which was aiming at prospective and logical observation of a community, to carry out demographic, public health and other research activities. HDSS is used as platform for other research activities. Further, platforms have been developed for data sharing within and HDSSs of the world managed by the INDEPTH Network (International Network for the Demographic Evaluation of Populations and Their Health in Developing Countries).

Functionality, reliability and data quality rely entirely on the size of budget for running program activities. Both household and individual data in communities can be used as a core for data sources related to health information that help to understand the actual health conditions expansively and systematically in communities. Biometric system is currently being used to identify individuals and for linkage purposes. Upcoming of eco-health research is influenced by the data collection system innovation and the surge of explorable data. Some technological limitations may occur, especially when dealing with the identification applications that use biometric system in cooperating large data. Ultimately, establishing a profound system for practice and development will be imperative for an eco-society for health systems. It will require collaborations among researchers with different expertise as well as data from various sources.

Procedure and impacts on public health of such system will be described here.

Keywords

HDSS Resident registration Surveillance system Vital statistics Personal identification Biometrics 

References

  1. 1.
    INDEPTH Network (2002) Population and health in developing countries. Volume 1. Population, health, and survival at INDEPTH sites, vol 1. International Development Research Centre, OttawaGoogle Scholar
  2. 2.
    Sankoh O (2010) Global health estimates: stronger collaboration needed with low- and middle-income countries. PLoS Med 7(11):e1001005CrossRefGoogle Scholar
  3. 3.
    Sankoh OA, Ngom P, Clark SJ, de Savigny D, Binka F (2006) Levels and patterns of mortality at INDEPTH demographic surveillance systems. In: Jamison DT, Feachem RG, Makgoba MW, Bos ER, Baingana FK, Hofman KJ, Rogo KO (eds) Disease and mortality in sub-Saharan Africa, 2nd edn. World Bank, Washington, DCGoogle Scholar
  4. 4.
    Verbal autopsy standards: ascertaining and attributing causes of death [http://www.who.int/healthinfo/statistics/verbalautopsystandards/en/]
  5. 5.
  6. 6.
  7. 7.
    Lewycka S, Mwansambo C, Kazembe P, Phiri T, Mganga A, Rosato M, Chapota H, Malamba F, Vergnano S, Newell ML et al (2010) A cluster randomised controlled trial of the community effectiveness of two interventions in rural Malawi to improve health care and to reduce maternal, newborn and infant mortality. Trials 11:88CrossRefGoogle Scholar
  8. 8.
    Hayes RJ, Alexander ND, Bennett S, Cousens SN (2000) Design and analysis issues in cluster-randomized trials of interventions against infectious diseases. Stat Methods Med Res 9(2):95–116CrossRefGoogle Scholar
  9. 9.
    Nevill CG, Some ES, Mung’ala VO, Mutemi W, New L, Marsh K, Lengeler C, Snow RW (1996) Insecticide-treated bednets reduce mortality and severe morbidity from malaria among children on the Kenyan coast. Tropical Med Int Health 1(2):139–146CrossRefGoogle Scholar
  10. 10.
    Hayes RJ, Moulton LH (2009) Clusiter randmised trials. Chapman & Hall/CRC, Boca RatonCrossRefGoogle Scholar
  11. 11.
    Garenne M, Das Gupta M, Pison G, Aaby P (1997) Introduction. In: Das Gupta M, Aaby P, Garenne M, Pison G (eds) Prospective community studies in developing countries. Clarendon press, OxfordGoogle Scholar
  12. 12.
    Schultz MG (1977) Joseph Goldberger and pellagra. Am J Trop Med Hyg 26(5 Pt 2 Suppl):1088–1092CrossRefGoogle Scholar
  13. 13.
    Kesler II, Levin ML (eds) (1970) The community as an epidemiologic laboratory: a case-book in community studies. Johns Hopkins Press, BaltimoreGoogle Scholar
  14. 14.
    Garenne M (1997) Three decades of research on population and health: the ORSTOM experience in rural Senegal, 1962–1991. In: Das Gupta M, Aaby P, Garenne M, Pison G (eds) Prospective community studies in developing countries. Clarendon press, Oxford, pp 235–252Google Scholar
  15. 15.
    Aziz KMA (1997) The history, methodology, and main findings of the Matlab project in Bangladesh. In: Das Gupta M, Aaby P, Garenne M, Pison G (eds) Prospective community studies in developing countries. Clarendon press, Oxford, pp 28–53Google Scholar
  16. 16.
    Kaneko S, Mushinzimana E, Karama M (2007) Demographic surveillance system (DSS) in Suba District, Kenya. Tropical Medicine and Health 35(2):37–40CrossRefGoogle Scholar
  17. 17.
    Rao C, Lopez AD, Hemed Y (2006) Causes of Death. In: Jamison DT, Feachem RG, Makgoba MW, Bos ER, Baingana FK, Hofman KJ, Rogo KO (eds) Disease and mortality in sub-Saharan Africa, 2nd edn. World Bank, Washington, DCGoogle Scholar
  18. 18.
    Hill K, Lopez AD, Shibuya K, Jha P, AbouZahr C, Anderson RN, Bawah AA, Betran AP, Binka F, Bundhamcharoen K et al (2007) Interim measures for meeting needs for health sector data: births, deaths, and causes of death. Lancet 370(9600):1726–1735CrossRefGoogle Scholar
  19. 19.
    Ghana VAST Study Team (1993) Vitamin A supplementation in northern Ghana: effects on clinic attendances, hospital admissions, and child mortality. Lancet 342(8862):7–12CrossRefGoogle Scholar
  20. 20.
    Hawley WA, Phillips-Howard PA, ter Kuile FO, Terlouw DJ, Vulule JM, Ombok M, Nahlen BL, Gimnig JE, Kariuki SK, Kolczak MS et al (2003) Community-wide effects of permethrin-treated bed nets on child mortality and malaria morbidity in western Kenya. Am J Trop Med Hyg 68(4 Suppl):121–127CrossRefGoogle Scholar
  21. 21.
    Binka FN, Indome F, Smith T (1998) Impact of spatial distribution of permethrin-impregnated bed nets on child mortality in rural northern Ghana. Am J Trop Med Hyg 59(1):80–85CrossRefGoogle Scholar
  22. 22.
    Agnandji ST, Lell B, Soulanoudjingar SS, Fernandes JF, Abossolo BP, Conzelmann C, Methogo BG, Doucka Y, Flamen A, Mordmuller B et al (2011) First results of phase 3 trial of RTS,S/AS01 malaria vaccine in African children. N Engl J Med 365(20):1863–1875CrossRefGoogle Scholar
  23. 23.
    Sankoh O, Byass P (2012) The INDEPTH network: filling vital gaps in global epidemiology. Int J Epidemiol 41(3):579–588CrossRefGoogle Scholar
  24. 24.
    Kaneko S, K’Opiyo J, Kiche I, Wanyua S, Goto K, Tanaka J, Changoma M, Ndemwa M, Komazawa O, Karama M et al (2012) Health and demographic surveillance system in the western and coastal areas of Kenya: an infrastructure for epidemiologic studies in Africa. J epidemiol/Jpn Epidemiol Assoc 22(3):276–285CrossRefGoogle Scholar
  25. 25.
    Kawakatsu Y, Kaneko S, Karama M, Honda S (2012) Prevalence and risk factors of neurological impairment among children aged 6–9 years: from population based cross sectional study in western Kenya. BMC Pediatr 12:186CrossRefGoogle Scholar
  26. 26.
    Komazawa O, Kaneko S, K’Opiyo J, Kiche I, Wanyua S, Shimada M, Karama M (2012) Are long-lasting insecticidal nets effective for preventing childhood deaths among non-net users? A community-based cohort study in western Kenya. PLoS One 7(11):e49604CrossRefGoogle Scholar
  27. 27.
    Matsuyama A, Karama M, Tanaka J, Kaneko S (2013) Perceptions of caregivers about health and nutritional problems and feeding practices of infants: a qualitative study on exclusive breast-feeding in Kwale, Kenya. BMC Public Health 13(1):525CrossRefGoogle Scholar
  28. 28.
    Wanyua S, Kaneko S, Karama M, Makokha A, Ndemwa M, Kisule A, Changoma M, Goto K, Shimada M (2014) Roles of traditional birth attendants and perceptions on the policy discouraging home delivery in coastal Kenya. East Afr Med J 91(3):83–93Google Scholar
  29. 29.
    Ndemwa M, Wanyua S, Kaneko S, Karama K, Anselimo M (2017) Nutritional status and association of demographic characteristics with malnutrition among children less than 24 months in Kwale County, Kenya. Pan Afr Med J 28(265)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Ecoepidemiology, Institute of Tropical MedicineNagasaki UniversityNagasakiJapan
  2. 2.NUITM-KEMRI Project, Kenya Research Station Nagasaki University Institute of Tropical Medicine (NUITM)NairobiKenya
  3. 3.Centre For Microbiology Research, KEMRINairobiKenya

Personalised recommendations