Organised Editing/Activities/Malaria Remote Populations - Mapping in South Eastern Madagascar

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Malaria Remote Populations - Mapping in South Eastern Madagascar

Introduction

Distance and travel time to health facilities in rural settings of the developing world are known drivers of care utilization, showing consistent negative impacts on the rates of diagnosis and treatment of many diseases, including malaria. In 2014, Madagascar had less than 3 clinicians (doctors, nurses and midwives) per 10,000 people. Access to health care is particularly low for populations living more than 5 km away from a health center, putting their children at higher risk for early childhood mortality. Malaria remains one of the leading causes of mortality in the island, and between 2016 and 2017, the country saw an increase of more than half a million cases. Yet, during that time, only 15.5% of children with reported fever had an RDT done and only 10.1% were treated with an antimalarial. Access to healthcare is particularly low in rural areas of the country, where over three quarters of the population live.

The USAID Malaria Remote Populations Activity, part of the Research, Innovation, Surveillance and Evaluation (RISE) Project, will help assess populations' travel time to public health facilities and understand geographic barriers for accessing care in several Districts of South Eastern Madagascar. As part of this activity, Institut Pasteur de Madagascar (IPM), the NGO PIVOT and Institut de Recherche pour le Development (IRD) are creating a basemap of all villages, buildings, footpaths, roads, waterways and rice fields in some Districts of South Eastern Madagascar. The maps will be used to obtain very precise estimations of travel time and geographic accessibility to health care facilities in these areas. The goal is to inform the design and implementation of interventions by the Madagascar Ministry of Public Health and its Partners aimed at improving access to malaria prevention, diagnosis and treatment for remote populations.

Approach

Our approach to the project is as follows:

  • We recruited 10 mappers with experience on mapping and geomatics, some of which had previously mapped in OSM
  • At the beginning of the project, the mappers received a series of on-hand training sessions with clear guidelines on OSM mapping
  • We use GeoHealth Tasking Manager, a program developed by IRD based on open access code adapted from the Tasking Manager of the Humanitarian OpenStreetMap Team (HOT)
  • Each district is divided into 2 or 3 projects and every project is divided into tasks of 1.26 km²
  • Mapping is done using JOSM
  • We use the Maxar standard as the imagery background or Bing imagery in case of clouds
  • Mappers open tasks in the Tasking Manager and map missing buildings, residential areas, rice fields, footpaths, roads and waterways (stream and river)
  • All individual buildings are mapped, whether isolated or as part of a residential area
  • Settlements with more than four (4) buildings are mapped as residential areas
  • All types of roads and small footpaths that local populations use to travel around rural areas are mapped. We refer to Highway Tag Africa in the OSM wiki for guidance on appropriate tagging of highways
  • We refer to Waterways in the OSM wiki for guidance on appropriate tagging of waterways
  • In terms of land use, we only map rice fields, but not other types of land use
  • Data quality is ensured via a multi-tiered validation process (see data quality section)

Data quality

To ensure data quality, all ten mappers hired for our project have university training in geography and geomatics, most at the masters’ level, and some had previous experience in OSM mapping. Several actions help ensure the quality of their work:

  • All mappers received an initial training on OSM mapping, the use of JOSM, and the Tasking manager interface
  • All mappers work together in the same space, which allows them to interact and solve problems
  • At the end of each task, the mappers run first the JOSM validator before submitting one task and they check errors if there are any. Then, they go back to the ID editor and activate the OSMOSE verification to check and correct any further errors before submitting it as a “mapped” task
  • After a task is marked as mapped, a second validation step is done by the most experienced members of our team (see list below), who check whether all geographic data is correctly mapped and fix any errors or missing data

Along the mapping process, two experienced supervisors oversee the progress and quality of the mapping done by the ten mappers. Separate from the validation step, supervisors visually inspect daily a high proportion of the tasks mapped and run similar diagnostics as described above to check that there are no errors left. Supervisors have frequent discussions with the mappers to ensure consistency in data creation across the team, identify any consistent or sporadic issues that may arise and solve them as a group. The goal is to produce high quality data that is usable for operational purposes on the field. We pay particular attention to the points below:

  • The building shadow should not be included in the building outline
  • Buildings may be very close but should not touch each other
  • A line should not connect to a polygon (e.g. a residential area or land use)
  • A road should always be connected to another road
  • A waterway should always be connected with another waterway, not to a land use.
  • When a road crosses through a stream or river with a bridge, we use the tag “bridge”, If no bridge is visible, we use the tag “ford”

Time frame

Mapping work began in July 5, 2021 due to end in July 31, 2022 for a duration of 13 months.

Mappers and Validators

List of mappers and validators are below:

Mappers Validators
1 Raoelisolonarivony (Optimus_Prime) 1 Felana Ihantamalala (Allyas) (supervisor/coordinator)
2 Koly Rabetsimialona (nicyK19) 2 Masiarivony Ravaoharimanga (Masiarivony) (supervisor)
3 Bienvenu Beriniaina (Dinaky) 3 Christophe Révillion (chris_seas)
4 Andriamihaja Rasolohery ( Mihaja) 4 Andriamihaja Rasolohery (Mihaja)
5 Miora Felaniaina Andrianandrasana (AxelRose21) 5 Judie Rajiabelina (Garrincha94)
6 Felana Ranaivomanana (Snoops92) 6 Safidy Rakotobe (Allpha)
7 Heritiana Randrianasolo (Heritiana10)
8 Safidy Rakotobe (Allpha)
9 Judie Rajiabelina (Garrincha94)
10 Diary Ramahatafandry (Sara Tancredi)

Contact

If you have any questions about this project, you can contact us via an email to the project’s principal investigator, Dr. Andres Garchitorena ([[1]]) or to the project coordinator, Dr. Felana Angella Ihantamalala ([[2]]).

Hashtag

We use the tags #geohealthresearch-project-XX #MRPactivity #pasteurMG #ird_fr #pivotmadagascar

Results

From July to September, a total of 3279 km2 have been mapped, comprising 100,050 buildings, 11,951 rice fields, 11,520 km of roads and footpaths, and 549 km of rivers and streams.