Using Climate monitoring and forecasts to improve malaria control in the Solomon Islands. — ASN Events

Using Climate monitoring and forecasts to improve malaria control in the Solomon Islands. (9322)

Lloyd Tahani 1 , Jason A Smith 2
  1. Solomon Islands Meteorological Service, Honiara, Solomon Islands, Solomon Islands
  2. Australian Bureau of Meteorology, Melbourne, Victoria, Australia

Over the past decade, extensive progress has been made on the control of malaria in the Solomon Islands due to the implementation of effective national control strategies. Notable success has been achieved in the provinces of Isabel and Temotu which are now considered to be in the malaria pre-elimination stage. However, in other parts of the country, including the heavily populated provinces of Guadalcanal and Malaita, the impact of malaria on the local population remains substantial.
Variability in malaria incidence is known to be strongly linked with climate, in particular rainfall, temperature and humidity. The use of rainfall and temperature indices in providing early warning of malaria outbreaks has become an established part of malaria monitoring and early warning systems in other parts of the world. In collaboration with COSPPac and the Vector-Borne Disease Control Program (VBDCP), the Solomon Islands Meteorological Service (SIMS) is working towards the implementation of an operational malaria monitoring and forecasting system based on rainfall and temperature.
The SIMS is the primary provider of climate information in the Solomon Islands, and operates a network of 8 meteorological stations across the country, with several more being added in the near future. These climate stations provide a vital long term rainfall and temperature record for the regions in which they are located. One of the core responsibilities of the SIMS climate section is to prepare and disseminate regular seasonal rainfall outlooks to key climate vulnerable sectors including agriculture, water resources and of course health. A long record of climate data for investigating the relationship between climate and malaria and a regular seasonal forecasting system are both essential to the development and success of a malaria early warning system.

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