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 | Algeria |
| Angola |
| Benin |
| Botswana |
| Burkina Faso |
| Burundi |
| Cameroon |
| Cape Verde |
| Central African Rep |
| Chad |
| Comoros |
| Congo |
| Côte d’Ivoire |
| Djibouti |
| DRC |
| Egypt |
| Equatorial Guinea |
| Eritrea |
| Eswatini |
| Ethiopia |
| Gabon |
| Gambia |
| Ghana |
| Guinea |
| Guinea-Bissau |
| Kenya |
| Lesotho |
| Liberia |
| Libya |
| Madagascar |
| Malawi |
| Mali |
| Mauritania |
| Mauritius |
| Morocco |
| Mozambique |
| Namibia |
| Niger |
| Nigeria |
| Rwanda |
| SADR |
| São Tomé and Príncipe |
| Senegal |
| Seychelles |
| Sierra Leone |
| Somalia |
| South Africa |
| South Sudan |
| Sudan |
| Tanzania |
| Togo |
| Tunisia |
| Uganda |
| Zambia |
| Zimbabwe |
| Reproductive, Maternal, Neonatal and Child Health |
| Adolescent Fertility Rate |
| Births Attended by Skilled Personnel |
| Contraceptive Prevalence |
| Infant Mortality Rate |
| DPT3 Immunization Coverage in Children |
| Maternal Mortality Ratio |
| Neonatal Mortality Rate |
| Pregnant Women with 4 ANC Visits |
| Stunting Under 5 yrs |
| Under-5 Mortality Rate |
| Unmet Need for Family Planning |
| Women Who Received Post-partum Care |
| HIV and AIDS |
| Adults Tested for HIV and Know Status |
| HIV Knowledge (Men aged 15-24 yrs) |
| HIV Knowledge (Women aged 15-24 yrs) |
| HIV Patients Receiving Anti-retroviral Drugs |
| HIV Positive Pregnant Women who Receive Antiretrovirals |
| HIV and TB Treatment |
| HIV Prevalence (Females 15-24 yrs) |
| Pregnant Women Tested for HIV and Know Status |
| School Attendance of Orphans |
| Condom Use |
| Malaria and Tuberculosis |
| Malaria Incidence |
| Malaria Deaths |
| Pregnant Women who Received 3 Doses of IPT |
| Under 5s Treated with Anti-Malarial Drugs |
| Under 5s who Slept Under ITN |
| Under 5s with Fever in Last 2 Weeks Screened for Malaria |
| TB Case Detection Rate |
| TB Treatment Success Rate |
| Health Finance |
| General Gov Exp on Health as % of GGE |
| Out of Pocket Health Expenditure |
| Per Capita Public Funds for Health |
| Full Name: | Incidence rate of Malaria |
| Full Unit: | per 100,000 population |
| Year-range of Data: | 2012 |
| Source: | Millennium Development Goals Indicators |
| Link : | http://mdgs.un.org/unsd/mdg/Data.aspx |
| Date Source Published: | 7th July 2014 |
| Date Source Accessed: | 23rd October 2014 |
 | The following countries had no data: |
This is the number of new cases of malaria reported each year per every 100,000 people.
Knowing the incidence rate of malaria is required for determining the need for treatment and services, particularly in more at-risk populations and in areas of limited resources. Changes in the incidence rate can indicate the burden of malaria on a population and allow for targeted interventions in high priority areas. Finally it can help to judge the success of malaria control programs and their implementation.
For countries with few cases of malaria, the reported cases by country surveillance systems are used. These are adjusted to account for under-reporting. Where malaria incidence is high or where surveillance data cannot be relied upon, estimates of new malaria cases derive from the number of people living in areas with high, low or no risk of malaria, based on results from studies that follow populations at risk of malaria over time.
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Alternative Data Sources
The data for each indicator on African Health Stats (AHS) are published by the UN agency, or UN inter-agency group, which holds responsibility for global monitoring of the indicator. This varies by indicator. Please refer to ‘Data Source’. AHS uses data from these sources because such data are internationally comparable and it is the mandate of those agencies to prepare such data and monitor progress internationally. In some cases the UN agency has made adjustments to the data in order to make national data internationally comparable, for example they may adjust national estimates to account for differences in survey design, the extent of potential underreporting, and the definition of what is being measured (eg. maternal deaths). This means that at times there may be discrepancies between national and international estimates. Individual countries may prefer to instead rely on national figures for national monitoring. For uniformity, AHS uses only international estimates of the UN agencies in data visualisations.
The following countries have communicated that they use alternative figures to monitor the indicator Malaria Incidence instead of the figures that appear in AHS data visualisations. The most recent alternative figure supplied by these countries, by source are: NA.
Collection Summary
For African countries with few cases of malaria, the number of cases reported by country surveillance systems is used. This information is adjusted to account for under-reporting (due to health services not reporting all cases, or infected individuals not using health services) and over-reporting (other diseases have the same symptoms as malaria). For countries where malaria incidence is high or where surveillance data cannot be relied upon, estimates of new malaria cases were derived from an estimate of the number of people living in areas with high, low or no risk of malaria, based on the result of studies that follow populations at risk of malaria over time. Estimates of new cases are adjusted downward for populations living in urban settings and to account for the expected impact of malaria prevention programmes.
