In 2023, Nigeria accounted for nearly 26 percent of all malaria cases worldwide, by far the highest share of any country. The Democratic Republic of the Congo had the second-highest share of malaria cases that year with 12.6 percent, followed by Uganda with 4.8 percent. Malaria is an infectious disease spread by female mosquitoes. Symptoms include fever, fatigue, vomiting, and headache and if left untreated the disease may lead to death. The region most impacted by malaria In 2023, there were a total of 263,000 cases of malaria worldwide. The region of Africa accounted for 246,000 of these cases, making it by far the region most impacted by this deadly disease. In comparison, Southeast Asia reported four thousand malaria cases in 2023, while the Americas had just 548. However, incidence rates of malaria have decreased around the world over the past couple decades. In Africa, the incidence rate of malaria decreased from 369 per 1,000 at risk in the year 2000 to 223 per 1,000 at risk in 2022. Worldwide, the incidence rate of malaria decreased from 79 to 60 per 1,000 at risk during this period. How many people die from malaria each year? Although rates of malaria have decreased around the world, hundreds of thousands of people still die from malaria each year, with the majority of these deaths in Africa. In 2023, around 597,000 people died from malaria worldwide, with 569,000 of these deaths occurring in Africa. However, death rates from malaria have decreased in Africa, with a rate of 62.5 per 100,000 at risk in the year 2015 compared to a rate of 52.4 per 100,000 at risk in 2023. In 2023, Nigeria accounted for around 31 percent of all malaria deaths, while 11 percent of such deaths were in the Democratic Republic of the Congo.

In 2023, approximately *** among one thousand inhabitants in Mali developed malaria. This statistic shows the 20 countries with the highest number of new malaria cases per 1,000 inhabitants at risk in 2023.

Malaria poses a risk to approximately 3.3 billion people or approximately half of the world's population. Most malaria cases occur in Sub-Saharan Africa. Asia, Latin America, and to a lesser extent the Middle East and parts of Europe are also affected. According to the Global Malaria Report published by the World Health Organization (WHO), malaria was present in 106 countries and territories in 2010; and there were 216 million estimated cases of malaria and nearly 0.7 million deaths - mostly among children living in Africa. In this research, we have estimated current population exposed to malaria - by country. In our computation, we have made the geographical distinction of areas with high, medium, low prevalence ("endemicity") of malaria in each country based on the Global malaria atlas compiled by the Malaria Atlas Project (MAP) of the Oxford University. The data are based on 24,492 parasite rate surveys (Plasmodiumfalciparum. 24,178; Plasmodium vivax. 8,866) from an aggregated sample of 4,373,066 slides prepared from blood samples taken in 85 countries. The MAP study employs a new cartographic technique for deriving global clinical burden estimates of Plasmodium falciparum malaria for 2007. These estimates are then compared with those derived under existing surveillance-based approaches to arrive at the final data used in the malaria mapping (Hay et al., 2009). (http://www.map.ox.ac.uk/media/maps/pdf/mean/World_mean.pdf, accessed 2012) Malaria maps generally separate the malaria endemicity into three broad categories by Plasmodium falciparum parasite rate (PfPR), a commonly reported index of malaria transmission intensity: PfPR < 5% as low endemicity, PfPR 5%-40% as medium/intermediate endemicity, and PfPR > 40% as high endemicity. In our research, global mapping techniques were used to estimate population exposed to malaria. The malaria endemicity maps were overlaid on global population maps from Landscan 20051 (Dobson, 2000) and country-level population exposure in the three endemicity areas were computed. Due to the spatial reference of the data and the number of observations in the combined data, the use of Geographic Information Systems functions from ESRI ArcGIS (v 9.3.1) were used and automated in the python (v 2.5) language.

Context

Africa, the world's second-largest continent, a continent with a wide array of vibrant cultures each with its own deep history, continent number 2 of largest population, and the continent is home to wonderful wildlife you can spot when you go on safari! Let's focus on Africa in this dataset.

Malaria is a common disease in Africa. The disease is transmitted to humans through infected mosquito bites. Although you can take preventive measures against malaria, it can be life-threatening. This dataset includes the malaria cases in African countries, the incidence at risk, and data on preventive treatments against malaria.

Content

This dataset includes data on all African countries from 2007 till 2017. Each country has a unique ISO-3 country code, and the dataset includes the latitude and longitude point of each country as well. The dataset includes the cases of malaria that have been reported in each country and each year, as well as data on preventive measures that have been taken to prevent malaria.

Acknowledgements

The data on the incidence of malaria, malaria cases reported, and preventive treatments against malaria have been retrieved from the world bank open data source.

Inspiration

Each country has a unique ISO-3 country code. You can use the ISO-3 code to create choropleth maps and in the geospatial analysis. In addition, the dataset includes latitude and longitude points for each country.

Drinking water safety and sanitation include a risk factor for malaria. Can improved drinking water facilities and preventive measures decrease the risk of malaria infection?

Check out my notebook submission, feel free to copy the kernel for your analysis: https://www.kaggle.com/lydia70/notebook-malaria-in-africa The notebook submission includes geospatial analysis with plotly.

BackgroundInfection by the simian malaria parasite, Plasmodium knowlesi, can lead to severe and fatal disease in humans, and is the most common cause of malaria in parts of Malaysia. Despite being a serious public health concern, the geographical distribution of P. knowlesi malaria risk is poorly understood because the parasite is often misidentified as one of the human malarias. Human cases have been confirmed in at least nine Southeast Asian countries, many of which are making progress towards eliminating the human malarias. Understanding the geographical distribution of P. knowlesi is important for identifying areas where malaria transmission will continue after the human malarias have been eliminated.Methodology/Principal FindingsA total of 439 records of P. knowlesi infections in humans, macaque reservoir and vector species were collated. To predict spatial variation in disease risk, a model was fitted using records from countries where the infection data coverage is high. Predictions were then made throughout Southeast Asia, including regions where infection data are sparse. The resulting map predicts areas of high risk for P. knowlesi infection in a number of countries that are forecast to be malaria-free by 2025 (Malaysia, Cambodia, Thailand and Vietnam) as well as countries projected to be eliminating malaria (Myanmar, Laos, Indonesia and the Philippines).Conclusions/SignificanceWe have produced the first map of P. knowlesi malaria risk, at a fine-scale resolution, to identify priority areas for surveillance based on regions with sparse data and high estimated risk. Our map provides an initial evidence base to better understand the spatial distribution of this disease and its potential wider contribution to malaria incidence. Considering malaria elimination goals, areas for prioritised surveillance are identified.

Malaria is a common and serious disease that primarily affects developing countries and its spread is influenced by a variety of environmental and human behavioral factors; therefore, accurate prevalence prediction has been identified as a critical component of the Global Technical Strategy for Malaria from 2016 to 2030. While traditional differential equation models can perform basic forecasting, supervised machine learning algorithms provide more accurate predictions, as demonstrated by a recent study using an elastic net model (REMPS). Nevertheless, current short-term prediction systems do not achieve the required accuracy levels for routine clinical practice. To improve in this direction, stacked hybrid models have been proposed, in which the outputs of several machine learning models are aggregated by using a meta-learner predictive model. In this paper, we propose an alternative specialist hybrid approach that combines a linear predictive model that specializes in the linear component of the malaria prevalence signal and a recurrent neural network predictive model that specializes in the non-linear residuals of the linear prediction, trained with a novel asymmetric loss. Our findings show that the specialist hybrid approach outperforms the current state-of-the-art stacked models on an open-source dataset containing 22 years of malaria prevalence data from the city of Ibadan in southwest Nigeria. The specialist hybrid approach is a promising alternative to current prediction methods, as well as a tool to improve decision-making and resource allocation for malaria control in high-risk countries.

BackgroundPrimaquine is a key drug for malaria elimination. In addition to being the only drug active against the dormant relapsing forms of Plasmodium vivax, primaquine is the sole effective treatment of infectious P. falciparum gametocytes, and may interrupt transmission and help contain the spread of artemisinin resistance. However, primaquine can trigger haemolysis in patients with a deficiency in glucose-6-phosphate dehydrogenase (G6PDd). Poor information is available about the distribution of individuals at risk of primaquine-induced haemolysis. We present a continuous evidence-based prevalence map of G6PDd and estimates of affected populations, together with a national index of relative haemolytic risk. Methods and FindingsRepresentative community surveys of phenotypic G6PDd prevalence were identified for 1,734 spatially unique sites. These surveys formed the evidence-base for a Bayesian geostatistical model adapted to the gene's X-linked inheritance, which predicted a G6PDd allele frequency map across malaria endemic countries (MECs) and generated population-weighted estimates of affected populations. Highest median prevalence (peaking at 32.5%) was predicted across sub-Saharan Africa and the Arabian Peninsula. Although G6PDd prevalence was generally lower across central and southeast Asia, rarely exceeding 20%, the majority of G6PDd individuals (67.5% median estimate) were from Asian countries. We estimated a G6PDd allele frequency of 8.0% (interquartile range: 7.4–8.8) across MECs, and 5.3% (4.4–6.7) within malaria-eliminating countries. The reliability of the map is contingent on the underlying data informing the model; population heterogeneity can only be represented by the available surveys, and important weaknesses exist in the map across data-sparse regions. Uncertainty metrics are used to quantify some aspects of these limitations in the map. Finally, we assembled a database of G6PDd variant occurrences to inform a national-level index of relative G6PDd haemolytic risk. Asian countries, where variants were most severe, had the highest relative risks from G6PDd. ConclusionsG6PDd is widespread and spatially heterogeneous across most MECs where primaquine would be valuable for malaria control and elimination. The maps and population estimates presented here reflect potential risk of primaquine-associated harm. In the absence of non-toxic alternatives to primaquine, these results represent additional evidence to help inform safe use of this valuable, yet dangerous, component of the malaria-elimination toolkit. Please see later in the article for the Editors' Summary

Central African Republic CF: Incidence of Malaria: per 1,000 Population at Risk data was reported at 305.540 Number in 2023. This records a decrease from the previous number of 306.370 Number for 2022. Central African Republic CF: Incidence of Malaria: per 1,000 Population at Risk data is updated yearly, averaging 387.165 Number from Dec 2000 (Median) to 2023, with 24 observations. The data reached an all-time high of 451.060 Number in 2005 and a record low of 305.540 Number in 2023. Central African Republic CF: Incidence of Malaria: per 1,000 Population at Risk data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Central African Republic – Table CF.World Bank.WDI: Social: Health Statistics. Incidence of malaria is the number of new cases of malaria in a year per 1,000 population at risk.;World Health Organization, World malaria report and Global Health Observatory Data Repository/World Health Statistics (http://apps.who.int/ghodata/).;Weighted average;This is the Sustainable Development Goal indicator 3.3.3[https://unstats.un.org/sdgs/metadata/].

Malaria Vaccines Market Outlook

According to our latest research, the global malaria vaccines market size reached USD 245 million in 2024, driven by the rising demand for effective malaria prevention strategies and growing global health initiatives. The market is expected to expand at a robust CAGR of 28.4% from 2025 to 2033, ultimately reaching a projected value of USD 2.19 billion by 2033. This remarkable growth is fueled by increased funding for malaria eradication programs, technological advancements in vaccine development, and supportive government policies, especially in malaria-endemic regions.

One of the primary growth factors for the malaria vaccines market is the increasing prevalence of malaria in tropical and subtropical regions, which continues to pose a significant global health challenge. Despite decades of control efforts, malaria remains a leading cause of morbidity and mortality, particularly among children under five and pregnant women. The persistent burden of the disease has spurred urgent demand for innovative preventive solutions, with vaccines emerging as a game-changing intervention. The World Health Organization’s endorsement of the RTS,S/AS01 (Mosquirix) vaccine and ongoing clinical trials of next-generation candidates have catalyzed market momentum. This surge in vaccine development activity is further bolstered by substantial investments from public–private partnerships, international organizations, and philanthropic entities, all focused on reducing malaria transmission and achieving long-term elimination goals.

Another significant driver for the malaria vaccines market is the rapid advancement of vaccine technologies, including recombinant protein, viral vector, and DNA-based platforms. These innovations have enabled the development of vaccines targeting multiple stages of the malaria parasite lifecycle, enhancing efficacy and broadening protective coverage. The integration of cutting-edge adjuvants and delivery systems has also improved immunogenicity and durability of vaccine-induced protection. Additionally, streamlined regulatory pathways and accelerated approval processes in high-burden countries are facilitating faster market entry for novel vaccines. The convergence of scientific breakthroughs and policy support is expected to sustain the marketÂ’s upward trajectory, with new candidates poised to address current limitations and expand access to life-saving interventions.

The malaria vaccines market is further propelled by the global focus on universal health coverage and equitable vaccine distribution. International health agencies, governments, and non-governmental organizations (NGOs) are prioritizing malaria vaccine deployment as part of broader disease control strategies. Large-scale pilot programs and routine immunization campaigns are being implemented across Africa, Asia, and Latin America, targeting high-risk populations and integrating malaria vaccines into existing healthcare infrastructures. The growing emphasis on public–private collaboration, capacity building, and supply chain optimization is expected to enhance vaccine accessibility, affordability, and uptake. These coordinated efforts are critical for achieving the World Health Organization’s targets for malaria reduction and elimination by 2030, providing a strong foundation for sustained market growth.

Regionally, the malaria vaccines market is dominated by sub-Saharan Africa, which accounts for the highest disease burden and the largest share of vaccine demand. However, significant opportunities are also emerging in the Asia Pacific and Latin America regions, where malaria remains endemic in several countries. North America and Europe, while contributing smaller market shares, play vital roles in research, funding, and technology transfer. Middle East & Africa is expected to exhibit the fastest market growth, supported by international funding and expanding immunization initiatives. The regional landscape is shaped by varying levels of healthcare infrastructure, regulatory frameworks, and disease epidemiology, underscoring the need for tailored market strategies and localized interventions.

Antimalarial Drugs Market Outlook

According to our latest research, the global antimalarial drugs market size reached USD 1.12 billion in 2024, reflecting steady demand driven by ongoing malaria prevalence and robust public health initiatives. The market is projected to grow at a CAGR of 4.7% during the forecast period, with the total market value anticipated to reach approximately USD 1.71 billion by 2033. This market expansion is primarily attributed to increasing malaria cases in endemic regions, the introduction of novel drug combinations, and enhanced governmental and non-governmental efforts toward malaria eradication.

A significant growth driver for the antimalarial drugs market is the persistent global burden of malaria, particularly in sub-Saharan Africa and parts of Southeast Asia. Despite advancements in vector control and prevention, malaria remains a top public health concern, with the World Health Organization (WHO) reporting over 249 million cases globally in 2023. The continued transmission of Plasmodium parasites, especially Plasmodium falciparum, necessitates a steady demand for effective antimalarial therapies. Ongoing outbreaks, drug resistance, and the emergence of new parasite strains further emphasize the need for innovative treatment options, fueling research and development within this sector. Additionally, multinational collaborations and funding from organizations such as the Global Fund and the Bill & Melinda Gates Foundation have bolstered the accessibility and affordability of antimalarial medications, particularly in low- and middle-income countries.

Another pivotal growth factor is the evolution of antimalarial drug formulations and combinations, particularly artemisinin-based combination therapies (ACTs). These therapies have become the gold standard in malaria treatment due to their high efficacy and ability to combat multidrug-resistant strains. Pharmaceutical companies are increasingly investing in research to develop next-generation ACTs and novel compounds targeting resistant malaria strains. Regulatory agencies and international health organizations have accelerated the approval and distribution of these advanced therapies, ensuring timely access in high-burden regions. The integration of digital health platforms and telemedicine has also facilitated prompt diagnosis and prescription, further supporting market growth by bridging gaps in healthcare delivery.

Public health initiatives, government policies, and international partnerships continue to be instrumental in expanding the reach of antimalarial drugs. National malaria control programs in endemic countries have prioritized the procurement and distribution of effective medications, often subsidized or provided free to vulnerable populations. Mass drug administration campaigns, community health worker training, and awareness programs have resulted in improved disease management and reduced mortality rates. The increasing emphasis on preventive measures, such as intermittent preventive treatment in pregnancy (IPTp) and seasonal malaria chemoprevention (SMC), has also contributed to a broader application of antimalarial drugs, thereby sustaining market demand.

Nifurtimox, traditionally used in the treatment of Chagas disease, has recently gained attention for its potential applications in malaria treatment. Researchers are exploring its efficacy as part of combination therapies to tackle drug-resistant malaria strains. The unique mechanism of action of Nifurtimox, which involves the generation of reactive oxygen species, offers a novel approach to combating Plasmodium parasites. This has sparked interest in its integration into existing antimalarial protocols, particularly in regions where resistance to conventional drugs is prevalent. The adaptability of Nifurtimox in treating various parasitic infections underscores its potential as a versatile therapeutic agent in the ongoing fight against malaria.

From a regional perspective, the Asia Pacific and Africa regions continue to dominate the antimalarial drugs market due to their high malaria burden and large at-risk populations. Africa, in particular, accounts for over 90% of global malaria cases and deaths, making it the largest consumer of antimalarial drugs. Efforts by governments and international agencies to st

BackgroundEvery 75 seconds, a child under five dies of malaria. Mainly children, aged between six months and five years, are at the highest risk for malaria. These children lost maternal immunity and did not yet developed specific immunity to the infection. Under the age of five, children bear the highest burden of malaria in Sub-Saharan Africa (SSA). Many individual and community level factors could contribute to malaria prevalence remaining high among under-five children in the region. Thus, this study aimed to assess the pooled prevalence of malaria among children aged 6–59 months and identify potential factors associated with malaria by using recent Malaria Indicator Surveys in 13 SSA countries.MethodsData for this study were drawn from recent 13 Sub-Saharan African countries Malaria Indicator Surveys (MIS). A total weighted sample of 60,541 children aged 6–59 months was included. STATA version 14.2 was used to clean, code and analyze the data. Multilevel logistic regression was employed to identify factors associated with malaria. Adjusted odds ratio with 95% CI and a P value

Climate change is a significant global challenge with major impacts on human health. It directly affects vector-borne diseases such as malaria by expanding vector ranges, boosting reproduction and biting rates, and shortening pathogen incubation periods. This study aimed to evaluate the association of temperature and precipitation with malaria transmission among children under five in Sub-Saharan Africa (SSA). We employed an analytical cross-sectional design to examine the relationship between temperature, precipitation, and malaria transmission among 15,009 children aged under five in six SSA countries: Burundi, Burkina Faso, Malawi, Nigeria, Tanzania, and Uganda. Historical climate data (temperature and precipitation) were retrieved from ERA-5 for the 12 months preceding the surveys. Weighted Modified Poisson regression model was used to assess the associations between climatic variables and malaria transmission. Malaria prevalence in the sample averaged 25.9%, with Nigeria (38.1%) and Burundi (38.0%) showing the highest rates. The results indicate that a one-degree Celsius rise in temperature increased malaria risk by 1.77-fold (95% CI: 1.297–2.414, p 

Abstract

Malaria is a significant public health problem in Kenya. More than 70% of the population is at constant risk from malaria, including those most vulnerable to the disease, specifically children and pregnant women. In the past 5 years, there has been a concerted effort by the government and malaria partnerships to fight the disease through prevention and treatment interventions such as mass and routine mosquito net distribution programs to attain universal coverage, intermittent preventive treatment for malaria during pregnancy, and parasitological diagnosis and management of malaria cases. The Kenya Malaria Indicator Survey is one of the key performance monitoring tools periodically used to provide an in-depth assessment of malaria control efforts over time. Kenya has in the past undertaken three Malaria Indicator Surveys, in 2007, 2010, and 2015. The results from these surveys provide information on the performance of the key malaria control interventions as experienced by communities across the country; and are crucial to evaluation of interventions. Moreover, they enable effective planning and malaria control programming and facilitate a good understanding of the factors, dynamics, and impediments that affect control efforts. The reports also provide evidence for comparison with other malaria control programs globally and allow for benchmarking to meet international standards and practices for combating the disease. In this regard, it is incumbent upon all partners and stakeholders in malaria control and elimination to embrace this report and assess the implications for malaria programming over the next few years.The report, therefore, has come at an opportune time when we are in the midst of implementing the Kenya Malaria Strategy 2019-2023. The results will form a basis for redirecting efforts and reorienting both technical and operational perspectives to address the challenges and strengthen the successes observed. The Ministry of Health is committed to further reducing the malaria burden in the coming years. Thus, I urge all players in malaria control to rededicate efforts and investments to enable delivery of sound malaria interventions and drive the burden further down towards our ambitious vision of a malaria-free Kenya within the shortest time possible

Geographic coverage

National

Analysis unit

Household and individuals

Universe

Sampled individuals and households

Sampling procedure

A sample is a group of people who have been selected for a survey. In the KMIS, the sample is designed to represent the national population age 15-49. In addition to national data, most countries want to collect and report data on smaller geographical or administrative areas. However, doing so requires a minimum sample size per area. For the 2020 KMIS the survey sample is representative at the national level, malaria endemicity zone, and for urban and rural areas. To generate statistics that are representative of the country as a whole and the five malaria endemicity zones, the number of women surveyed in each malaria endemicity zone should contribute to the size of the total (national) sample in proportion to size of the malaria endemicity zone. However, if some malaria endemicity zones have small populations, then a sample allocated in proportion to each malaria endemicity zone’s population may not include sufficient women from each district for analysis. To solve this problem, malaria endemicity zones with small populations are oversampled. For example, let’s say that you have enough money to interview 6,771 women and want to produce results that are representative of Kenya as a whole and its malaria endemicity zones (as in Table 2.11). However, the total population of Kenya is not evenly distributed among the malaria endemicity zones: some malaria endemicity zones, such as Low risk zone, are heavily populated while others, such as Coast endemic zone are not. Thus, Coast endemic zonemust be oversampled

Mode of data collection

Face to face using CAPI

Snapshot img { margin: 10px !important; } The anti-malarial medicines market share is expected to increase by USD 287.52 million from 2020 to 2025, and the market’s growth momentum will accelerate at a CAGR of 5%. This anti-malarial medicines market research report provides valuable insights on the post COVID-19 impact on the market, which will help companies evaluate their business approaches. The anti-malarial medicines market report also offers information on several market vendors, including AstraZeneca Plc, Bayer AG, Cipla Inc., F. Hoffmann-La Roche Ltd., GlaxoSmithKline Plc, Mylan NV, Novartis AG, Pfizer Inc., Sanofi SA, and Sun Pharmaceutical Industries Ltd. among others. Furthermore, this report extensively covers anti-malarial medicines market segmentation by product (artemisinin compounds, quinolines and related compounds, and other compounds) and geography (Asia, ROW, Europe, and North America).

What will the Anti-malarial Medicines Market Size be During the Forecast Period?

Download the Free Report Sample to Unlock the Anti-malarial Medicines Market Size for the Forecast Period and Other Important Statistics

Anti-malarial Medicines Market: Key Drivers, Trends, and Challenges

The strong funding to eradicate malaria is notably driving the anti-malarial medicines market growth, although factors such as drug-resistant pathogens may impede the market growth. Our research analysts have studied the historical data and deduced the key market drivers and the COVID-19 pandemic impact on the anti-malarial medicines industry. The holistic analysis of the drivers will help in deducing end goals and refining marketing strategies to gain a competitive edge.

Key Anti-malarial Medicines Market Driver

One of the key factors driving growth in the anti-malarial medicines market is the growing incidence of malaria. The growing incidence of malaria has increased the need for malaria rapid diagnostic devices, which can provide rapid test results and help in the diagnosis of the disease. The number of malaria cases is higher in Africa and Southeast Asian countries, owing to the lack of adequate healthcare infrastructure and less knowledge about parasitic infectious diseases. In 2018, the CDC reported that malaria was endemic in 91 countries and subtropics. According to WHO, there were almost 229 million cases globally of malaria in 2019. According to the OECD, about 2.3 million people across the world are at risk from malaria. Around 1 billion people in APAC, such as that in Papua New Guinea, Solomon Islands, Pakistan, India, Nepal, the Philippines, Indonesia, Myanmar, the Lao PDR, Cambodia, Thailand, China, Vietnam, Bangladesh, the Republic of Korea, and Malaysia, are at high risk of malaria. According to a report published by the CDC in 2019, around 219 million estimated cases of malaria were reported across the world. In addition, in the US, approximately 1,700 cases are diagnosed every year. To support and provide early diagnosis and treatment, CDC provides information related to malaria through its CDC Division of Parasitic Diseases and Malaria diagnostic website, which is available 24 hours a day.

Key Anti-malarial Medicines Market Trend

The development of prophylactic treatment is an antimalarial medicines market trend that is expected to have a positive impact in the coming years. The global anti-malarial medicines market is currently dominated by artemisinin compounds and by quinoline and its derivatives. These compounds are helpful only if the disease is effectively diagnosed, which itself is a challenge because of the complex life cycle of the disease. To overcome this, the market is inching toward developing a preventive mechanism against malaria in the form of various vaccines. All these years, the focus was on developing therapeutics for the treatment of malaria. However, the malaria parasites have a complex life span, and the current therapeutics do not offer lifelong protection. To overcome this challenge, many vaccines are being developed, some of which are expected to be marketed during the forecast period. For instance, RTS,S/AS01 by GlaxoSmithKline is an advanced malaria vaccine candidate. The development of such advanced treatment methods will fuel the growth of the global anti-malarial medicines market during the forecast period.

Key Anti-malarial Medicines Market Challenges

Drug-resistant pathogens are a major hindrance to the anti-malarial medicines market growth. Human malaria is caused mainly by four Plasmodium species, such as P. vivax, P. falciparum, P. ovale, and P. malariae. Some of these species are resistant to a single drug, while some are resistant to multiple drugs. This increases the probability and severity of the disease. Multidrug-resistant microbes are a major threat to human health currently. Such microbes change themselves to protect against the antimicrobial agent used, thereby developing resistance to the drug. This happens primarily due to the irrational u

Africa accounts for only 2.3% of the global coronavirus disease 2019 (COVID-19) cases and 4% of deaths, but this relative low incidence has been partly attributed to the limited testing capacity in most countries. In addition, the population in many African countries is also at high risk of infection with multiple diseases such as HIV, tuberculosis and malaria. It is therefore important to know the real spread of SARS-CoV-2 in Africa and its co-occurrence with other pathogens. The aim of this study is to determine the prevalence and circulation of SARS-CoV-2 variants, and the frequency of co-infection with the malaria parasite. For this purpose, we conducted serological point of care tests and microscopy examinations on 998 volunteers of different ages and sexes in a random and stratified population sample in Burkina-Faso. In addition, nasopharyngeal swab samples were taken for molecular detection of SARS-COV-2 by RT-qPCR and for whole viral genome sequencing. Our results show a 3.2% and a 2.5% of SARS-CoV-2 seroprevalence and PCR positivity, respectively; and 22% of malaria incidence over the sampling period (from August to November 2020). There were no significant differences in SARS-CoV-2 prevalence between male and female subjects, but we report marked differences linked to age. The age group most frequently infected by SARS-CoV-2 was people above 40 years (6.9%; 95% CI 3.7–10.1), whereas malaria was much more frequent in children aged below 12 years (42.2%; 95% CI 36.1–48.4). Importantly, we found 2 cases of confirmed co-infection (PCR positive) and 8 cases of suspected co-infection (seropositive/PCR negative) mostly in children and teenagers. Finally, we report the genome sequences of 13 SARS-CoV-2 isolates circulating in Burkina Faso at the time of analysis, which were assigned to lineages A.19, A.21, B.1.1.404, B.1.1.118, B.1 and grouped into clades; 19B, 20A and 20B. This is the first population-based study about SARS-CoV-2 and malaria prevalence and co-infection performed in Burkina Faso during the first wave of the pandemic. In addition, this study provides a relevant estimation of the real prevalence of SARS-CoV-2 and variants circulating in this Sub-Saharan African country. Besides, it highlights the low frequency of malaria co-infection in African communities.

The population estimated to be at risk of contracting malaria in Honduras fluctuated between nine and around 90 percent during the period analyzed, with the last year depicted accounting for the lowest value. In 2023, Brazil was the country that accounted for the highest share of malaria cases in Latin America.

Abstract

The 2020 Kenya Malaria Indicator Survey (2020 KMIS) was a cross-sectional household-based survey with a nationally representative sample of conventional households. The survey targeted women age 15-49 and children age 6 months to age 14 living within conventional households in Kenya. All women age 15-49 who were usual members of the selected households or who spent the night before the survey in the selected households were eligible for individual interviews. In all sampled households, children age 6 months to age 14 were tested for anaemia and malaria.

The sample for the 2020 KMIS was designed to produce reliable estimates for key malaria indicators at the national level, for urban and rural areas separately, and for each of the five malaria endemic zones.

The 2020 KMIS was designed to provide information on the implementation of core malaria control interventions and serve as a follow-up to the previous malaria indicator surveys. The specific objectives of the 2020 KMIS were as follows: - To measure the extent of ownership of, access to, and use of mosquito nets - To assess coverage of intermittent preventive treatment of malaria during pregnancy - To examine fever management among children under age 5 - To measure the prevalence of malaria and anaemia among children age 6 months to age 14 - To assess knowledge, attitudes, and practices regarding malaria control - To determine the Plasmodium species most prevalent in Kenya

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-14
• Woman age 15-49

Universe

The survey covered all de jure household members (usual residents), women age 15-49 years and children age 0-14 years resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2020 KMIS followed a two-stage stratified cluster sample design and was intended to provide estimates of key malaria indicators for the country as a whole, for urban and rural areas, and for the five malaria-endemic zones (Highland epidemic prone, Lake endemic, Coast endemic, Seasonal, and Low risk).

The five malaria-endemic zones fully cover the country, and each of the 47 counties in the country falls into one or two of the five zones as follows: 1. Highland epidemic prone: Kisii, Nyamira, West Pokot, Trans-Nzoia, Uasin Gishu, Nandi, Narok, Kericho, Bomet, Bungoma, Kakamega, and Elgeyo Marakwet 2. Lake endemic: Siaya, Kisumu, Migori, Homa Bay, Kakamega, Vihiga, Bungoma, and Busia 3. Coast endemic: Mombasa, Kwale, Kilifi, Lamu, and Taita Taveta 4. Seasonal: Tana River, Marsabit, Isiolo, Meru, Tharaka-Nithi, Embu, Kitui, Garissa, Wajir, Mandera, Turkana, Samburu, Baringo, Elgeyo Marakwet, Kajiado, and West Pokot 5. Low risk: Nairobi, Nyandarua, Nyeri, Kirinyaga, Murang’a, Kiambu, Machakos, Makueni, Laikipia, Nakuru, Meru, Tharaka-Nithi, and Embu.

The survey utilised the fifth National Sample Survey and Evaluation Programme (NASSEP V) household master sample frame, the same frame used for the 2015 KMIS. The frame was used by KNBS from 2012 to 2020 to conduct household-based sample surveys in Kenya. It was based on the 2009 Kenya Population and Housing Census, and the primary sampling units were clusters developed from enumeration areas (EAs). EAs are the smallest geographical areas created for purposes of census enumeration; a cluster can be an EA or part of an EA. The frame had a total of 5,360 clusters and was stratified into urban and rural areas within each of 47 counties, resulting into 92 sampling strata with Nairobi and Mombasa counties being wholly urban.

The survey employed a two-stage stratified cluster sampling design in which, in the first stage of selection, 301 clusters (134 urban and 167 rural) were randomly selected from the NASSEP V master sample frame using an equal probability selection method with independent selection in each sampling stratum. The second stage involved random selection of a fixed number of 30 households per cluster from a roster of households in the sampled clusters using systematic random sampling.

For further details on sample design, see Appendix A of the final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Four types of questionnaires were used for the 2020 KMIS: the Household Questionnaire, the Woman’s Questionnaire, the Biomarker Questionnaire, and the Fieldworker Questionnaire. The questionnaires were adapted to reflect issues relevant to Kenya. Modifications were determined after a series of meetings with various stakeholders from DNMP and other government ministries and agencies, nongovernmental organisations, and international partners. The Household and Woman’s Questionnaires in English and Kiswahili were programmed into Android tablets, which enabled the use of computer-assisted personal interviewing (CAPI) for data collection. The Biomarker Questionnaire, in English and Kiswahili, was filled out on hard copy and then entered into the CAPI system.

Cleaning operations

The 2020 KMIS questionnaires were programmed using Census and Survey Processing (CSPro) software. The program was then uploaded into Android-based tablets that were used to collect data via CAPI. The CAPI applications, including the supporting applications and the applications for the Household, Biomarker, and Woman’s Questionnaires, were programmed by ICF. The field supervisors transferred data daily to the CSWeb server, developed by the U.S. Census Bureau and located in Nairobi, for data processing on the central office computer at the KNBS office in Nairobi.

Data received from the field teams were registered and checked for any inconsistencies and outliers on the central office computer at KNBS. Data editing and cleaning included an extensive range of structural and internal consistency checks. All anomalies were communicated to field teams, which resolved data discrepancies. The corrected results were maintained in the central office computer at KNBS head office. The central office held data files which was used to produce final report tables and final data sets. CSPro software was used for data editing, cleaning, weighting, and tabulation.

Response rate

A total of 8,845 households were selected for the survey, of which 8,185 were occupied at the time of fieldwork. Among the occupied households, 7,952 were successfully interviewed, yielding a response rate of 97%. In the interviewed households, 7,035 eligible women were identified for individual interviews and 6,771 were successfully interviewed, yielding a response rate of 96%.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2020 Kenya Malaria Indicator Survey (KMIS) to minimise this type of error, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2020 KMIS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2020 KMIS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS, using programs developed by ICF. These programs use the Taylor linearisation method of variance estimation for survey estimates that are means, proportions, or ratios.

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Completeness of reporting - Births by calendar years - Number of enumeration areas completed, by month and malaria endemicity - Positive rapid diagnostic test (RDT) results, by month and malaria endemicity - Concordance and discordance between RDT and microscopy results - Concordance and discordance between national and external quality control laboratories

See details of the data quality tables in Appendix C of the final report.

HRP2/LDH Combo Malaria Rapid Tests Market Outlook

According to our latest research, the Global HRP2/LDH Combo Malaria Rapid Tests market size was valued at $420 million in 2024 and is projected to reach $810 million by 2033, expanding at a CAGR of 7.4% during the forecast period of 2025–2033. The primary growth driver for this market is the increasing prevalence of malaria in endemic regions, coupled with global health initiatives focused on early and accurate diagnosis. The demand for rapid diagnostic solutions, particularly those that can distinguish between different Plasmodium species, is rising sharply as public health agencies and governments intensify efforts to control and eventually eradicate malaria. The HRP2/LDH combo tests are gaining prominence due to their superior sensitivity and specificity, which are crucial for timely and effective malaria management.

Regional Outlook

Sub-Saharan Africa remains the region with the largest share of the HRP2/LDH Combo Malaria Rapid Tests market, accounting for nearly 55% of the global market value in 2024. This dominance is attributed to the persistently high burden of malaria, robust support from international health organizations, and widespread adoption of rapid diagnostic tests (RDTs) in national malaria control programs. The mature healthcare infrastructure in certain African nations, combined with aggressive policy frameworks and funding from global initiatives such as the Global Fund and WHO, has facilitated the large-scale deployment of combo RDTs. Moreover, local manufacturing initiatives and tailored distribution networks have further strengthened the market’s foothold in this region, ensuring steady growth and high market penetration.

The Asia Pacific region is emerging as the fastest-growing market, with a projected CAGR of 8.9% from 2025 to 2033. Countries such as India, Indonesia, and Myanmar are witnessing a surge in malaria cases, prompting governments and NGOs to invest heavily in advanced diagnostic technologies. The increasing focus on rural healthcare outreach, coupled with rising awareness among healthcare providers, is fueling demand for HRP2/LDH combo tests. Furthermore, regional collaborations and investments in local manufacturing are reducing costs and improving supply chain efficiency, making these diagnostics more accessible. The presence of a large population at risk and ongoing efforts to eliminate malaria by 2030 in several Asia Pacific countries are key factors driving this accelerated growth.

Emerging economies in Latin America and parts of the Middle East & Africa are gradually ramping up the adoption of HRP2/LDH combo malaria rapid tests, albeit facing unique challenges. In these regions, issues such as limited healthcare funding, inadequate diagnostic infrastructure, and logistical barriers hamper widespread deployment. However, localized demand is rising as governments recognize the economic and social impact of malaria and prioritize disease surveillance and control. Policy reforms aimed at improving healthcare access, along with targeted donor funding and technical support from international agencies, are expected to enhance market penetration. Nonetheless, the pace of adoption remains uneven, with some countries progressing faster than others due to differences in regulatory environments and resource allocation.

Report Scope

Association of climatic and socio-demographic factors with malaria transmission.

The population estimated to be at risk of contracting malaria in Brazil fluctuated between nine and 23 percent during the period analyzed. In the last year depicted, an estimated 11 percent of the population in the South American country was considered to be at risk of contracting malaria. In 2023, Brazil was the country that accounted for the highest share of malaria cases in Latin America.