Innovative tools and OpenHDS for health and demographic surveillance on Rusinga Island, Kenya

BMC Research Notes

Nicolas Maire³  Willem Takken⁴  Wolfgang R. Mukabana²  Collins Mweresa¹  Alexandra Hiscox⁴  Kelvin Onoka¹  Ibrahim Kiche¹  Aurelio Di Pasquale³  Tobias Homan⁴ 

[1] Department of Medical Entomology, International Centre of Insect Physiology and Ecology, Nairobi, Kenya;School of Biological Sciences, University of Nairobi, Nairobi, Kenya;University of Basel, Basel, Switzerland;Laboratory of Entomology, Wageningen University and Research Centre, Wageningen, The Netherlands

关键词: Kenya;    Malaria;    Data management platform;    Mobile data collection;    Health and demographic surveillance system;   

Others  :  1230420
DOI  :  10.1186/s13104-015-1373-8

 received in 2015-03-18, accepted in 2015-08-24,  发布年份 2015

【 摘 要 】

Background

Health in low and middle income countries is on one hand characterized by a high burden associated with preventable communicable diseases and on the other hand considered to be under-documented due to improper basic health and demographic record-keeping. health and demographic surveillance systems (HDSSs) have provided researchers, policy makers and governments with data about local population dynamics and health related information. In order for an HDSS to deliver high quality data, effective organization of data collection and management are vital. HDSSs impose a challenging logistical process typically characterized by door to door visits, poor navigational guidance, conducting interviews recorded on paper, error prone data entry, an extensive staff and marginal data quality management possibilities.

Methods

A large trial investigating the effect of odour-baited mosquito traps on malaria vector populations and malaria transmission on Rusinga Island, western Kenya, has deployed an HDSS. By means of computer tablets in combination with Open Data Kit and OpenHDS data collection and management software experiences with time efficiency, cost effectiveness and high data quality are illustrate. Step by step, a complete organization of the data management infrastructure is described, ranging from routine work in the field to the organization of the centralized data server.

Results and discussion

Adopting innovative technological advancements has enabled the collection of demographic and malaria data quickly and effectively, with minimal margin for errors. Real-time data quality controls integrated within the system can lead to financial savings and a time efficient work flow.

Conclusion

This novel method of HDSS implementation demonstrates the feasibility of integrating electronic tools in large-scale health interventions.

【 授权许可】

   
2015 Homan et al.

【 图 表 】

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