Category: Malaria

Reveal takes aim at malaria parasite through mass drug administration campaigns in Southern Province, Zambia

Reveal takes aim at malaria parasite through mass drug administration campaigns in Southern Province, Zambia

By Parysa Oskouipour on September 18, 2019 in Health Data Systems, Malaria, News

Deep in Zambia’s Southern Province, in a town a three-hour drive away from the district’s largest city and economic hub (Siavonga), lies Manchamvwa Health Facility. This clinic serves as the focal point for the health needs of hundreds of people who live in the surrounding villages, and as such, is often overwhelmed with the many health needs of its patients. Malaria season in particular tends to put a great strain on the facility, with peak periods in previous years seeing anywhere from 100 to 200 cases per month.

Over the last couple of years, the Government of the Republic of Zambia (GRZ), with the assistance of Akros and PATH’s Bill and Melinda Gates Foundation-funded Malaria Control and Elimination Partnership in Africa (MACEPA), have been working with the National Malaria Elimination Program district staff to overcome these numbers and improve the health of the local community by using geospatial technology to optimize indoor residual spraying (IRS) campaigns. Recently, the two organizations teamed up again to be the first to ever use Reveal’s spatial intelligence approach to maximize reach and ensure accountability in a mass drug administration (MDA) campaign that distributed antimalarials to the doorstep of each community member in three districts of Southern Province.

Lake Kariba’s still, glistening waters at sunset.

The recent history of malaria in Southern Province is one of resounding progress thus far. Due to its proximity to Lake Kariba’s glistening, still water, it is unfortunately a heavily malaria-burdened region by nature. But malaria in this region is highly seasonal, linked to the annual arrival of rainfall from December to April, leaving ample overgrowth and standing water—prime mosquito-breeding real estate. This seasonality provides an attractive window through which most interventions have taken aim. The result has been an impressive decrease in prevalence of malaria parasitaemia among children less than five years of age, from 15.5% in 2006, to 5.5% in 2010, and 0.0% in 2018.1,2 Trends like these make Southern Province appealing as a prime candidate for malaria elimination. However, despite overall improvement in the province’s malaria burden at large, districts directly adjacent to the lake are still at higher risk, as malaria cases have shown to be persistently high in some health facilities despite ongoing interventions.

To propel Southern Province closer to elimination, in 2014 MACEPA supported the national program with a malaria MDA research study in the Southern Province districts lining Lake Kariba, an area with an estimated population of 300,000 people. The rapid malaria reduction in the study area resulted in Zambia adding MDA to its arsenal of interventions in 2017. The country’s experience of malaria MDA—two rounds with one month in between doses­—has shown it to be an effective intervention in areas with a strong foundation of vector control, case management, and surveillance. Recognizing that MDA campaigns are most effective when every household and individual in the targeted region are reached, MACEPA engaged Akros for its technical expertise in introducing Reveal as a novel approach to maximize the impact of MDA for malaria control and elimination in this area.

Finding a village never before visited by IRS

Finding a village never before visited by IRS

By Ernest Mulenga on April 16, 2019 in Malaria, News

Background

The Reveal tool is more than just a mobile data collection tool that improves data quality and timeliness. The tool provides spray teams with maps to navigate to areas that might otherwise be difficult to find. These maps are highly accurate and complete, made through our satellite enumeration process. The district mop-up teams are especially reliant on these maps. Mop-up teams are teams designated by the district with the specific task of revisiting areas that were not sprayed well during an initial visit or areas that were missed completely.

Unsurprisingly, mop-up teams help more areas reach the coverage goal of 90% sprayed and these teams visit some of the most remote villages, some of which have never been visited before. Ernest Mulenga, an Akros Surveillance Officer, documents the Chadiza’s mop-up team visit to a village; because the the team relies heavily on maps to navigate, they adopt vernacular of mapping and navigation, referring to the villages by the codes assigned to the “polygon” shapes appearing on the maps.

The search for polygon 01-455

It was the 9th of November 2017 when the mop-up team left Chadiza IRS base in search of Polygon 01-455 under Mtaya catchment area, which is located to eastern side of Chadiza district about 45 km from the district main post office.

Passing through Ngala area under Miti catchment, the team made a first stop at polygon 01-457 around 11:00 before proceeding to 01-455. The team used the GPS locator on the Reveal application, to navigate to a road that would lead to the village. Discovering the road to be impassable due to flooding from the heavy rain, the team was re-directed by locals to a path that went through the mountain and was said to be passable with a vehicle.

The Mtaya catchment area. The spray team was progressing through this area when they found polygon 01-455, which had never before been visited by a spray team.

The journey through the mountain started off well. After climbing some distance, however, the path became too filled with potholes for the Land Cruiser to continue. The team was left with no choice but to complete the journey on foot. At this point the team felt that they had covered a considerable distance with the Cruiser and that the polygon must not be far off. Thus, the team began to move with the aid of a GPS on the tablet. Once the direction of walking was set, the tablet was switched off for fear of using too much battery power.

Operationalizing spatial intelligence means saving lives

Operationalizing spatial intelligence means saving lives

By Anna Winters on March 21, 2019 in Health Data Systems, Malaria

As a spatial epidemiology PhD student, I was drawn to questions about how the environment relates to and facilitates vector-borne disease (diseases that are spread by vectors like mosquitos). These questions and interests tend to lead spatial epidemiology graduate school students (like I was) straight into the land of building spatial models. We effectively try to understand how measures like wetness, greenness, and elevation may combine mathematically to tell us where high numbers of mosquitoes live. If those mosquitoes live near human hosts, or even animals, there may be greater risk of vector-borne diseases.

So, I too built a lot of maps and models during graduate school. I mapped the risk of West Nile virus (WNV) in Colorado, USA. At the time, WNV had, somewhat shockingly, erupted in that region of the US. I also modeled human plague in Uganda—effectively developing maps to precisely depict areas at high and low risk of plague transmission. “Target interventions where it’s red” was the more-or-less summary, where red equaled high-risk areas. Point made. Thesis closed. Safe on the shelf.

But here I sit on the other end of the world, far away from hallowed academic halls that are often lined with dead dissertations and theses like mine. Here in southern Africa, disease transmission is much more tangible. Before, I read about death rates due to malaria and HIV from my school in Colorado, US. Here, I witness the impact of those death rates every day when I drop my kids off at school—new graves being dug closer and closer to the road. I am involved with a local school that is inundated with orphans and vulnerable children—even from one of the more affluent regions of Zambia. In this environment, high morbidity and mortality rates are incessant. Help is highly dependent on securing increasingly limited resources. Navigating the challenging logistics of getting those resources to the right people at the right time and in the right place are often broken. However, despite the acute need to target limited resources, mapping approaches like the one I developed in school are rarely seen nor used to inform interventions.

It is time for the public health community—both globally and locally—to do business differently. It’s time to more appropriately lean on the idea of spatial intelligence through epidemiological and map-based approaches to inform the practice of intervention planning and delivery. Academic, math-based modeling can lend a good understanding of where and how we should focus our limited resources to save the most lives. “Why aren’t these approaches being actively used?” you might ask. Part of the challenge is a lack of tools and finite planning approaches to translate maps and models into operational, boots on the ground, public health programming decisions. Questions like, “Where are all the houses located?,” “Which houses exactly should receive the intervention based upon the model output?,” and “Has the intervention effectively reached everywhere it was targeted?” are challenging to assess, particularly in regions like here in southern Africa, where so many areas consist of rural villages with no addresses.