Malaria is one of the world’s most common infectious diseases and leading cause of death in many developing countries. Malaria, caused by Plasmodium parasites, tends to cause symptoms such as fever, chills, and flu-like illness. Left untreated, the mosquito-borne disease can develop severe complications such as kidney and liver damage, spleen rupture and sometimes death. In 2022, malaria caused an estimated 247 million clinical episodes and 619,000 deaths. Despite the fact that access to malaria prevention and treatment has improved over the past two decades, several obstacles—including medicine and pesticide resistance—remain to make malaria control efforts in hard-hit areas more difficult, slowing down progress in many nations.

The World Health Organization (WHO) recently introduced the first malaria vaccine for broad use in young children, which is a promising development. However, malaria surveillance makes the foundation for disease control and prevention since the continuous and systematic collection, analysis, and interpretation of disease-specific data can help to monitor changing disease patterns, design effective health interventions, and estimate the burden of disease. Several technological advancements have been made to aid the global response to combat malaria epidemics. In 2021, Zzapp Malaria, a startup company had collaborated with IBM to develop an AI-powered mobile application that enables customization in malaria elimination interventions of African towns and villages. Leveraging weather data and satellite images, the company predicts the formation and evaporation of water bodies where malarian mosquitoes might breed and affect the whole region. In sub-Saharan Africa, the company's technology has been used and tested in pilot projects in Ghana, Tanzania, Zanzibar, and Ethiopia. These projects were made possible by partnerships with regional partners, including local governments, foundations, and NGOs.

Innovative Technologies for Malaria Surveillance & Monitoring

Malaria-Visanalytics: A Tool for Visual Exploratory Analysis of Brazilian Public Malaria Data

Techniques for data integration and visualization have been extensively employed in scientific research to support difficult or protracted research issues and enable the use of vast volumes of data. Integration enables the collection of data from several sources into a single database that contains variables useful for various study kinds. Thanks to visualization, large and complicated data sets can be handled and interpreted more conveniently. Malaria-VisAnalytics (MVA) enables users to visualize and evaluate static data. Users of MVA have the option to interactively explore and contrast data using a variety of methods and dimensions.

The objective of MVA is to make it simple for users to discover significant insights rapidly and easily into the data with minimal effort, while also giving researchers a platform to share data, visualizations, and insights, ask questions related to problems, and speed up and improve decision-making. Health professionals can profit from a variety of visual resources, from a more global chlorophetic visualization that enables them to analyze how a given variable changes from one region to another to more focused visualizations, like a network graph that demonstrates the connections between numerous nodes.

The Brazilian government has databases such as SIVEP and SINAN that collect information both inside and outside of the Brazilian Amazonian region for malaria episodes. SIVEP is a database that houses information on malaria cases that have been reported to hospitals and doctors' offices in the Brazilian Amazonian area. The database contains 5,490,603 records with 43 attributes, spanning the years 2003 to 2017. Outside of the Amazonian region, SINAN epidemiological surveillance system records cases of more than twenty dangerous diseases, including malaria. The database contains 42,670 records with 79 attributes, spanning the years 2003 to 2018. With the rise of web interfaces based on geographic mapping, the potential of geo-localization technologies will become clearer.

NGS and CRISPR: Advancing Malaria Surveillance

In the past few years, molecular biology and genomics have revolutionized biology and medicine. The Next Generation Sequencing (NGS) and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) are two significant technologies expected to have an influence on the surveillance and diagnosis of malaria. NGS, also known as high-throughput or massive parallel sequencing, enables the targeted or whole genome sequencing and analysis of millions to billions of DNA or RNA fragments. In order to effectively monitor large numbers of samples, routine malaria surveillance programs could benefit from implementing NGS technologies.

By combining epidemiological data with improvements in malaria genomes (especially those based on NGS) and related bioinformatics tools, the ability to detect and monitor the spread of the disease may be increased. With the aid of these methods, many studies of parasite populations, antimalarial drug resistance, monitoring of hrp2/3 gene deletions, and assessing the results of ongoing and upcoming therapies can be made easier. There is an urgent need for studies using these techniques, and if they are scaled up, they could be crucial for monitoring transmission in order to achieve effective control and the eventual objective of eliminating malaria.

Thanks to improvements in NGS technologies, it is now possible to generate high quality and sensitive data supported by bioinformatic tools and increased accessibility to epidemiological data. This data may be used to detect changes in transmission intensity, identify multi-genomic infections, assess the effectiveness of interventions, and spot potential weaknesses in malaria control programs in both high and low transmission areas. Determining the number of parasite strains, genetic diversity as well as relatedness and genetic structure of parasites in an infection, might lead to an increased understanding.

The use of P. falciparum diagnostic techniques based on CRISPR has the potential to completely transform malaria surveillance in Africa. The detection of both symptomatic and asymptomatic infections as well as any associated resistance mutations will be greatly aided by this method's capacity to identify as few as one copy of the target DNA per reaction. CRISPR has already been used to detect malaria strain variants in mixed infections, a significant obstacle for attempts to control and eradicate malaria.

Mobile-based Technologies for Malaria Detection

Many smart mobile applications, Short Message Service based apps and Unstructured Supplementary Service Data (USSD) based applications have been developed to integrate the use of cell phones into a routine malaria prevention and control program for improving the management of malaria cases. In India, the Mobile-based Surveillance Quest using IT (MoSQuIT) is being utilised to automate and streamline malaria surveillance for all parties involved, including medical officers and public health decision-makers as well as health workers in rural India. Health facilities in Zanzibar are using the revolutionary Malaria Epidemic Early Detection System (MEEDS) to report new cases of malaria using mobile devices. The Zanzibar Malaria Elimination Programme is using Coconut Surveillance, an open-source mobile software programme created by malaria experts, exclusively for the control and elimination of malaria. With a focus on malaria and other health issues, the SMS for Life effort, a "public-private" project uses common technology to put an end to stock-outs and enhance access to necessary medicines in sub-Saharan Africa.

To promote malaria monitoring in Myanmar, the National Malaria Case-Based Reporting App (MCBR) was developed for mobile phones. The Net4Schs App, an Android application used for data collection, processing, and reporting on School Long-lasting Insecticidal Nets (LLINs) distribution operations, is one example of a mobile app that has been used to facilitate the distribution of medications. Additionally, apps have been created to promote malaria screening and diagnosis. For instance, the NLM Malaria Screener is a diagnostic tool that helps users track their malaria symptoms and diagnose the disease.

Recently, Uganda-based start-up Matibabu has created a non-invasive method for diagnosing and detection of malaria leveraging mobile technology and light sensor. The Matibabu smartphone application does the test in about 60 seconds and sends the results right to the patient's doctor. By shining light through the patient's finger, the test is conducted. Results are affirmative if the sensor detects a change in light intensity after the beam passes through red blood cells. Patients can then text their doctor with the findings. Every time a test is administered, the phone's GPS location will be logged, making it simpler to identify the sources of infection. Additionally, the app offers general preventive advice as well as a sound-based insect repellant that may be used or deactivated as needed.

Drone-based Technologies to Support Malaria Interventions

Drones, or unmanned aerial vehicles (UAVs) are playing a major role in mosquito surveillance, identification, and treatment. From developing genetically based vector control tools to identifying larvae sites, delivering massive aerial spraying to providing drugs and vaccines, drones have proved to a promising tool in managing malaria in Kenya, Tanzania, India, Rwanda, and Zanzibar. In general, container breeders like Aedes aegypti and Aedes albopictus (malaria-causing mosquito breeds) lay their eggs in a variety of water-filled containers, whereas non-container breeders like Culex species are linked to stagnant water rich in organic matter, and Anopheles species prefer artificial water bodies like fishponds, irrigated rice fields, and mining ponds. These profiles are crucial for both ground truthing and training remote sensing systems to enable the detection of breeding locations.

In Zanzibar, Agras MG-1S drones were utilized to spray 10 L of Aquatain, a biodegradable chemical that has been used to coat drinking water basins to limit the larvae and reduce the number of adult mosquitoes that can transmit malaria. Besides, DJI Phantom drones are being used to investigate and locate mosquito breeding sites in Malawi and close to Lake Victoria. In an ongoing experiment in Burkina Faso using "gene drive" technology, genetically altered mosquitoes will be released in an effort to eradicate the disease's female carriers.

Other Notable Projects

Malaria Atlas Project (MAP)

Understanding the distribution of malaria is vital for its prevention and eradication. The primary mission of MAP is to assemble spatial databases (describing human population distribution) and map the limits of malaria transmission and malaria endemicity within that range. Evaluating burden, trends, and impact helps support informed decision-making for better malaria control at local, national, and international levels.

SolarMal: Solar Power for Malaria Eradication

Use of insecticides against mosquitoes and medications to treat infection has remained the primary pillars of malaria control programs, but the long-term success and sustainability of both strategies are endangered by the emergence of pesticide and medication resistance. Hence, it is necessary to research brand-new complementing control strategies. The SolarMal project involves the use of odour-baited traps for malaria control, which operate according to a counterflow mechanism. Alluring mosquitoes to the traps mimicking human odorants could help realize a decline malaria transmission. The innovative technology employed in 4500 traps in Rusinga, on Lake Victoria has helped to eliminate mosquitoes and malaria infection, decreasing malarial infections approximately 30%. SolarMal Mosquito Trapper sucks the mosquitoes into trap through the solar-powered ventilator, which created a flow of air into the trapper. The technology is applicable to other mosquito-borne illnesses such as Zika virus, dengue fever, etc.

FeverTracker

FeverTracker application records on-the-ground details about malaria incidences linked to geographic positioning data, geotagged pictures, and other pertinent data in accordance with the required format. FeverTracker offers bilingual data support to meet regional needs and promote inclusive use. The software includes extensive symptom information as well as use scenarios. There is also a warning about prescribing medication based on user symptoms. An interactive web portal for data visualisation, summaries, and downloads is connected to the mobile app. While requesting permission to use text messages, mobile data, local storage, and location data, the software complies with privacy laws and policies. FeverTracker is connected to SMS text message and an advising instruction system in addition to automatic data collection to alert the district or state response center in accordance with federal regulations.

Way Ahead

The use of artificial intelligence tools, machine learning techniques, and mobile technologies for malaria surveillance programs is expected to increase in the coming years. Growing advancements in biology can help scientist reduce turnaround time for malaria research and make the existing tools more effective in understand its potential to spread malaria.

According to Techsci Research report on “India Antimalarial Drugs Market By Drug Class (Aryl Aminoalcohol Compounds, Antifolate Compounds, Artemisinin Compounds, Others), By Mechanism of Action (Treatment for Malaria, Prevention from Malaria), By Distribution Channel (Hospital Pharmacy, Retail Pharmacy, Online Pharmacy), Region, Competition, Forecast & Opportunities, 2018-2028F” India Antimalarial Drugs Market is expected to grow steadily between 2024 and 2028, with an impressive CAGR. This can be attributed to the high prevalence of malaria, rising healthcare expenditure and increasing research & development activities.