Integrating Weather Monitoring into KEMRI/CDC HDSS in Western Kenya

Project Name: Integrating Weather Monitoring into KEMRI/CDC HDSS in Western Kenya

Project Status: Proposed

Point of Contact: Emily Zielinski-Gutierrez

Center: CGH

Keywords: Climate change, weather database, adaptation, early warning system

Project Description: KEMRI field station in western Kenya has been the collaborative research site for CDC-Kenya research and program activities for 30 years, generating data informing international policy on malaria, HIV, Rotavirus, TB, and other diseases of global importance. The CDC-supported KEMRI Health and Demographic Surveillance System (HDSS) is the population platform providing essential baseline measures for CDC branches, defining disease prevalence, defining environmental and disease risk factors, testing interventions and developing public health programs. CDC technically and financially supports HDSS mortality ascertainment using verbal autopsy to examine disease trends, and define future priorities. Clearly the epidemiology of some of these diseases is influenced by weather and climate, however more accurate data are required as the only routinely generated data available for the KEMRI/CDC HDSS site is from the airport 40-100km away. In order to analyze patterns of relationship between weather and disease risk, and to move toward development of models that could provide early warning of enhanced disease risk or extreme weather events such as drought or flooding, we seek to integrate routine ascertainment of weather parameters using new technologies. This project aims to integrate real-time monitoring of weather parameters such as rainfall, humidity and temperature in the KEMRI/CDC HDSS using automatic weather stations installed in 3 sites within the demographic surveillance area.

Impact of project

• The data will be used to validate remote sensing data available in online data portals
• Assess relationship of weather variables with climate sensitive diseases such as malaria
• Help in adaption to climate change through development of early warning systems for disease and extreme weather such as drought which leads to malnutrition

Scalability –
The data collected will be stored within the KEMRI/CDC HDSS database and any CDC project can request access. Furthermore, this may provide a model for the better integration of disease surveillance and earth observation platforms.

Project rationale and description: HDSS is resource intense and new technologies are sought to speed data access, and increase data application, including remotely. The study will be conducted at three KEMRI/CDC HDSS areas of Asembo, Gem and Karemo in western Kenya, an area approximating 700km2. The HDSS population is ~230,000 persons, living in predominantly rural, impoverished areas, with poor infrastructure, with some clusters of peri-urban villages.

Suitable and affordable automatic weather station equipment with data loggers similar to the one illustrated in the figure below will be procured for the three HDSS areas. The weather stations will collect precipitation, temperature, humidity and wind direction data every 15 minutes throughout each 24 hours. The equipment will come with an inbuilt modem to connect with a remote server which is located at the main KEMRI-CDC research offices in Kisian, Kisumu.

We will configure the stations to use the GPRS protocol using SIM cards for data transmission from the stations to the data center. Suitable places that are secure, representative and have no obstruction will be identified for the installation of the weather stations. Data will be downloaded to field supervisor’s tablets and uploaded to the data center if instant data connection fails. The HDSS field supervisors and community interviewers will be trained on the handling of the equipment to ensure flawless collection of data. Following training, we will pilot test the equipment. We will create an online data portal for real-time data access. Data analysts will perform regular quality control checks on the data to ensure completeness and consistency.

Measure of success

• Consistent high quality rainfall, temperature and humidity data for the KEMRI/CDC HDSS study area
• Data used for development of early warning systems for malaria and extreme events/environmental conditions leading to malnutrition
• Analysis of relationships between weather and climate sensitive diseases from parallel real-time systems (eg malaria)
• Online accessible weather pattern data for the HDSS study area

For more information about this project, please contact the CHIIC at chiic@cdc.gov or Brian Lee at brian.lee@cdc.hhs.gov.