Zzapp Malaria

AI for planning, executing, and monitoring of large-scale, cost-effective anti-malaria operations

Past and Current Partners

First place ($3M) in the IBM Watson XPRIZE AI for Good competition, Cisco Global Problem Solver 2021, Google for Startups SDGs

Active Countries
Ghana, São Tomé
Thematic area(s)
Health
Technology
SaaS, but projects typically includes on-the-ground project management, quality control, training, and other services.
Organisation Name
Zzapp Malaria
READ MORE ON THEIR WEBSITE

The Problem

Killing, every year, hundreds of thousands, sickening millions and greatly impeding developing economies, malaria is one of the worst problems in Africa. Nonetheless, malaria has been eliminated after successful operations in many countries, specifically, well resourced countries. A key method in these operations was thorough treatment of the water bodies in which mosquitoes breed. Such operations require significant investment, but completely resolve, rather than merely manage the problem. Zap Malaria developed an artificial intelligence-based system that enables the planning and execution of operations that are highly cost-effective even in Africa’s most challenging conditions.

The Solution

Zzapp Malaria considers malaria to be one of the world’s biggest solvable problems. An artificial intelligence-based system for planning, executing, and monitoring of large-scale, cost-effective anti-malaria operations

How it works?

  • Step 1: Planning: our artificial intelligence analyzes satellite images to locate houses and areas with high probability of the presence of water bodies, and uses climate data to recommend the best seasonality for launching the operation. Based on the system’s recommendations, as well as our entomological and epidemiological analysis, we devise a nationwide strategy.
  • Step 2: Assigning - the system automatically divides the areas that will be treated to “chunks†of 1002 meters, and assigns them to field workers. Step 3: Mapping - field workers use the app to navigate through the areas they were assigned, and map (and sometimes sample) water bodies they locate. Information is uploaded automatically to the system.
  • Step 4: Treatment - field workers: 1. treat the water bodies that were detected; 2. Spray houses that were recommended by the system; and 3. Place light traps and sugar traps in locations recommended by the system. Data is uploaded automatically to the system. Step 5: Monitoring - the system flags undertreated areas and/or areas in which reduction of mosquitoes is insufficient.
Digital X Solution Zzapp Malaria

Bridging the digital divide

Zzapp intentionally designed their artificial intelligence to include all communities, in all areas. For example theirhouse-detection algorithm detects not only modern houses (prevalent, for example, in Ghana) but also traditionally built huts (prevalent, for instance, in Malawi). Zzapp works well both on less advanced smartphones and in areas with weak internet infrastructure and limited access to power sources. Furthermore, the app uses iconography in addition to text, to make it accessible to low-literacy audiences, and to maximize the efficiency of field workers. They have discovered that for many of their workers the app is a first-time encounter with digital technology, and that the training they receive from them is a significant source of empowerment for them in many additional areas. The app is very user-friendly, so that the average training, even of high-school graduates who lack technological literacy, takes no longer than a few hours. Furthermore, it works on inexpensive phones available in low-income countries, can work offline when in the field, and conserves battery life.

Impact and highlights

In 2021, in a controlled trial in an urban area in Obuasi, Ghana, covering more than 200,000 people, Zzapp reduced the mosquito population by 60% for a cost that was 4% of conventional mosquito removal. In 2022, in a randomized controlled trial in districts with *both urban and rural areas* in São Tomé, covering more than 130,000 people, Zzapp reduced the mosquito population by 67% and malaria prevalence by 40% for a cost that was 20% of conventional mosquito removal.

Plans for expansion

Zzapp aims to work with all countries where malaria is present. Currently in discussions with government officials in Rwanda; the vice minister of health of Equatorial Guinea; and, in Kenya, together with the government, Zzapp launched a pilot in collaboration with KEMRI and ICIPE (leading local research institutions). Zzapp is also working with Goodbye Malaria (an international NGO) in Mozambique and have proposed a collaboration with ABT Associates for a project in Ethiopia. Their target countries are those where malaria poses the heaviest health burden - namely Nigeria, Niger, Chad, Uganda, and DRC. In the mid-term we hope to apply our solution outside of sub-Saharan Africa, to other countries including Guyana and Suriname, as well as Solomon islands, Papua New Guinea, Thailand, India, and Cambodia.