Impact of security context on mobile clinic activities : a GIS multi criteria evaluation based on an MSF humanitarian mission in Cameroon

Abstract

Humanitarian crises require a quick and effective emergency response to answer the needs of vulnerable populations. Deploying mobile health clinics in the field is an example of an outreach activity that can be undertaken for this purpose. This study is based on a real mission implemented by a medical international aid organization (MSF or Médecins Sans Frontières) in Cameroon during the recent Central African Republic humanitarian crisis (2014). All of the knowledge and information required for the analysis have been collected by field observations, interviews and the experiences of the author of this thesis during a 4-month emergency mission in East Cameroon, working as a mobile clinic manager.

The selection of the most suitable mobile clinic sites is a complicated task in such a volatile context. One mobile team can typically cover a number of 8 sites in a two week rotation period (1 site per day, visited every 14 days). Due to a sensitive security and humanitarian situation, a significant number of factors need to be considered before making any decision. This paper shows how GIS can be used to help define the most suitable sites and to what extent the security related factors can affect the final strategy.

Using a Multi Criteria Decision Analysis (MCDA), suitable site areas were identified inside the study boundary via two different analyses: (i) with security considerations and (ii) with no security considerations. Through an Analytic Hierarchy Process (AHP), 13 criteria were divided into three distinctive classes (security related factors, human related factors and environmental factors). AHP helped determine the influence and weight of each factor to one another with pairwise comparisons. It has the advantage of structuring the analysis in a simple and comprehensive way for the decision makers. A Weighted Linear Combination (WLC) completed the AHP method to aggregate the factors and classes together according to their respective weights. A final raster map was generated for each analysis and reclassified into 20 ranges of equal intervals based on the suitability value of each cell. Alternatives were ranked according to their suitability range.
First, the three highest ranges of values were identified as the most suitable areas given security considerations. They cover 1714 km² (3,7 % of the study area) and include 19 relevant towns for mobile health activities.

Second, five of the highest ranges of values were identified as the most suitable areas with no security considerations. They cover 1893 km² (4 % of the study area) and include 18 relevant towns for mobile health activities.
Both analyses only share 10 sites which indicates that the security context significantly affects the site selection in a humanitarian context.

The first analysis (i) was also compared with the actual activities implemented by MSF in 2014 (without the use of GIS). The comparison shows that 9 of the 12 most pertinent sites selected by the MSF decision makers during the 2014 emergency (most visited sites by the mobile clinics) were also selected with the GIS analysis.
The research shows that GIS can be an added value for selecting suitable sites for health mobile activities in a humanitarian context.
MCDAs such as AHP proved to be an effective approach to help in the prioritization process and to limit the alternatives for decision makers. Similar analyses can be used in the future and we suggest keeping them simple and well-structured, especially when dealing with emergency crises where influencing factors are subject to very rapid change.

Popular Abstract

Humanitarian crises require a quick and effective emergency response to answer the needs of vulnerable populations. Deploying mobile health clinics in the field is an example of an outreach activity that can be undertaken for this purpose. This study is based on a real mission implemented by a medical international relief organization (MSF or Médecins Sans Frontières) in Cameroon during the recent humanitarian crisis in Central African Republic (2014).The knowledge and information required for this study have been collected by field observations, interviews and the experiences of the author of this research during a 4-month emergency mission in East Cameroon, where he worked as a mobile clinic manager.

The selection of the most suitable mobile clinic sites is a complicated task in volatile contexts like the one in Eastern Cameroon during the 2014 refugee crisis. Due to a sensitive security and humanitarian situation, a significant number of factors need to be considered for setting mobile clinics. The expertise by international humanitarian staff working in the field is an asset to improve the efficiency of medical and logistical operations. At the same time, humanitarian organizations such as MSF try to improve their approach by testing and applying new methods to improve their response to people in need. The use of cartographic tools such as GIS (Geographical Information System) is definitely helpful to the teams on the ground, whether it be to map uncharted regions, deploy teams during epidemics or track the past and current activities implemented by the organisation in the past. Furthermore, more advanced geographic analyses could also be beneficial to the medical activities provided that reliable data is collected.
This study shows how GIS can be used to help define the most suitable sites to implement mobile clinics and reflects on the extent to which security-related factors can affect the final strategy.

Methodology
Site selection for mobile clinics in a humanitarian context can be affected by different criteria related to security, human activities and environment. In order to consider the several factors into the analysis, a method known as Multi Criteria Decision Analysis (MCDA) was used. Suitable site areas were identified inside the study boundary via two different analyses: one analysis considering security-related factors and one analysis that does not taken into account security-related factors.
The GIS software allows taking into account different criteria, overlay them together and extract a final map where the most suitable areas to set up mobile clinics are highlighted.
Results

In the first analysis (considering security-related factors), the GIS method helped the author to identify an area of 1,714 km² as highly suitable, including 19 towns where mobile health activities could be implemented.
In the second analysis (where security-related factors were not considered), an area of 1,893 km² was identified as highly suitable, including 18 towns where mobile health activities could be implemented.
However, the two analyses did not highlight the same towns since only 10 are shared in common. This outcome indicates that security-related factors have a strong influence on the results and thus they do affect the activities of mobile clinics activities and the strategies of MSF decision-makers.

In the study, the results of the first analysis were also compared with the actual activities implemented by MSF in 2014 (without the use of GIS) in order to see whether the GIS is a pertinent tool to help in the decision-making process of selecting sites for mobile clinics. The comparison shows that 9 of the 12 most visited sites by the MSF team during the 2014 emergency in Eastern Cameroon were also selected by the GIS analysis. It therefore suggests that cartographic analyses can provide pertinent results to help implementing health activities in a humanitarian context, considering that factors influencing the location of the activities can rapidly change due to security conditions.

• author: Muller, Vincent
• supervisor: Mohammadreza Rajabi
• organization: Dept of Physical Geography and Ecosystem Science
• alternative title: Impact of Security Context on MSF Mobile Clinic Activities in Cameroon
• course: GISM01 20161
• year: 2016
• type: H2 - Master's Degree (Two Years)
• subject: Earth and Environmental Sciences
• keywords: Physical Geography and Ecosystem analysis, GIS, AHP, MCDA, Humanitarian, Security, MSF
• publication/series: Master Thesis in Geographical Information Science
• report number: 50
• language: English
• id: 8876389
• date added to LUP: 2016-06-02 09:58:13
• date last changed: 2016-06-02 09:58:13