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

Homan T, Di Pasquale A, Kiche I, Onoka K, Hiscox A, Mweresa C, Mukabana WR, Takken W, Maire N - BMC Res Notes (2015)

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

View Article: PubMed Central - PubMed

Affiliation: Laboratory of Entomology, Wageningen University and Research Centre, Wageningen, The Netherlands. tobias.homan@wur.nl.

ABSTRACT

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.

No MeSH data available.


Related in: MedlinePlus

Project sticker with barcode on the doorpost of a house: Barcode scanning, integrated into the mobile data collection, allows quick identification of locations and study population to add or amend health and demographic information
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Fig3: Project sticker with barcode on the doorpost of a house: Barcode scanning, integrated into the mobile data collection, allows quick identification of locations and study population to add or amend health and demographic information

Mentions: To ensure that FWs are adding data to the correct corresponding house and individual in the field in subsequent follow up surveys, each house was provided with a door sticker showing its unique ID (Fig. 3). The unique ID is also expressed as a barcode which is scanned with the tablet on arrival at the house and recorded in the data base. Once scanned, the barcode is validated against existing barcodes in the mobile application of OpenHDS and the application allow questionnaires to be filled in and stored. Each household is visited three times a year to collect and update demographic and malaria-related data. Members of the HDSS team visit all residential structures in nine geographic areas on the island simultaneously taking approximately three months to cover their area. At all households observed pregnancies, new births, deaths and migrations which have occurred since the previous visit are recorded and updated. Digital questionnaires concerning demographic information are consistent with the HDSS questionnaire format of the INDEPTH network (See Table 1). Moreover, the standardized questionnaire formats are widely used in East Africa and Kenya and therefore apply well to our research site.Fig. 3


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

Homan T, Di Pasquale A, Kiche I, Onoka K, Hiscox A, Mweresa C, Mukabana WR, Takken W, Maire N - BMC Res Notes (2015)

Project sticker with barcode on the doorpost of a house: Barcode scanning, integrated into the mobile data collection, allows quick identification of locations and study population to add or amend health and demographic information
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4556052&req=5

Fig3: Project sticker with barcode on the doorpost of a house: Barcode scanning, integrated into the mobile data collection, allows quick identification of locations and study population to add or amend health and demographic information
Mentions: To ensure that FWs are adding data to the correct corresponding house and individual in the field in subsequent follow up surveys, each house was provided with a door sticker showing its unique ID (Fig. 3). The unique ID is also expressed as a barcode which is scanned with the tablet on arrival at the house and recorded in the data base. Once scanned, the barcode is validated against existing barcodes in the mobile application of OpenHDS and the application allow questionnaires to be filled in and stored. Each household is visited three times a year to collect and update demographic and malaria-related data. Members of the HDSS team visit all residential structures in nine geographic areas on the island simultaneously taking approximately three months to cover their area. At all households observed pregnancies, new births, deaths and migrations which have occurred since the previous visit are recorded and updated. Digital questionnaires concerning demographic information are consistent with the HDSS questionnaire format of the INDEPTH network (See Table 1). Moreover, the standardized questionnaire formats are widely used in East Africa and Kenya and therefore apply well to our research site.Fig. 3

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

View Article: PubMed Central - PubMed

Affiliation: Laboratory of Entomology, Wageningen University and Research Centre, Wageningen, The Netherlands. tobias.homan@wur.nl.

ABSTRACT

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.

No MeSH data available.


Related in: MedlinePlus