Previous work conducted by MAP and other groups has relied on geolocated parasite rate surveys as the raw data input to statistical models used to predict the global burden of malaria. These surveys are the easiest and most reliable source of data to use for statistical modelling. However, while there are many parasite rate surveys available for sub-Saharan African countries, surveys beyond that region are scarcer. Even within sub-Saharan Africa, surveys in a given country might be extensive geographically but limited temporally. Concerns over potential increases in the numbers of cases in recent years cannot be addressed by parasite rate surveys conducted several years ago.
Data from countries’ routine surveillance systems are increasingly being made available online. Furthermore, new statistical models being developed by MAP allow these data to be used alongside or instead of survey point data. These data are typically reported for a given sub-national administrative unit (for example state, country, province) and for a given time period (yearly, quarterly, monthly, or weekly). In many cases, there is a useful breakdown into species, patient age-bands, and sex.
The new models use annual parasite incidence (API) per 1000 head of population as the raw input. The ROAD-MAP team has been engaged in a wide-ranging data gathering exercise to obtain the data required to calculate API. To date, we have gathered the data required to calculate in excess of 150,000 national and sub-national values for API globally for the years 2000-2017. We are exploring the possibility of releasing these data, pending discussions concerning permissions. For more information, please see our surveillance data page.
In addition to gathering information on cases, we are also gathering data on deaths and interventions.
Under the country profiles, we have listed all the sources we have found for these routine surveillance data, including links to online resources and publications.