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Accepted for/Published in: JMIR Public Health and Surveillance

Date Submitted: Nov 4, 2024
Open Peer Review Period: Nov 4, 2024 - Dec 30, 2024
Date Accepted: Feb 19, 2025
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Analyzing Satellite Imagery to Target Tuberculosis Control Interventions in Densely Urbanized Areas of Kigali, Rwanda: Cross-Sectional Pilot Study

Faccin M, Geenen C, Happaerts M, Ombelet S, Migambi P, André E

Analyzing Satellite Imagery to Target Tuberculosis Control Interventions in Densely Urbanized Areas of Kigali, Rwanda: Cross-Sectional Pilot Study

JMIR Public Health Surveill 2025;11:e68355

DOI: 10.2196/68355

PMID: 40273403

PMCID: 12045519

Analyzing satellite imagery to target tuberculosis control interventions in densely urbanized areas of Kigali, Rwanda: pilot study

  • Mauro Faccin; 
  • Caspar Geenen; 
  • Michiel Happaerts; 
  • Sien Ombelet; 
  • Patrick Migambi; 
  • Emmanuel André

ABSTRACT

Background:

Early diagnosis and treatment initiation for tuberculosis (TB) not only improve individual patient outcomes, but also reduce circulation within communities. Active case-finding (ACF), a cornerstone of TB control programs, aims to achieve this by targeting symptom screening and laboratory testing to individuals at high risk of infection. However, its efficiency is dependent on its ability to accurately identify such high risk individuals and communities. The socio-economic determinants of TB include difficulties in accessing healthcare and high within-household contact rates. These two determinants are common in the poorest neighborhoods of sub-Saharan cities, where household crowding and lack of healthcare access often coincide with malnutrition and HIV infection, further contributing to the burden of tuberculosis.

Objective:

In this study we propose a new approach to enhance the efficacy of ACF with focused interventions that target subpopulations at high risk. In particular we focus on densely inhabited urban areas, where the proximity of individuals represents a proxy for poorer neighborhoods with enhanced contact rates.

Methods:

To this end, we used satellite imagery of the city of Kigali, Rwanda, to identify areas with a high density of small residential buildings. We subsequently screened 10,423 people living in these areas for TB exposure and symptoms and referred patients with a higher risk score for PCR testing.

Results:

We found autocorrelation in questionnaire scores for adjacent areas, up to 782 meters, suggesting that risk for TB can be associated with geographic areas. Out of 202 people with high questionnaire scores, 9 tested positive.

Conclusions:

Our results suggest that analyzing satellite imagery may allow the identification of urban areas where inhabitants are at higher risk of TB. Such results could be used to guide targeted active case-finding interventions. Clinical Trial: The protocol was approved by Rwanda National ethic Committee IRB 00001497 of IORG0001100 and Written informed consent obtained from each participant.


 Citation

Please cite as:

Faccin M, Geenen C, Happaerts M, Ombelet S, Migambi P, André E

Analyzing Satellite Imagery to Target Tuberculosis Control Interventions in Densely Urbanized Areas of Kigali, Rwanda: Cross-Sectional Pilot Study

JMIR Public Health Surveill 2025;11:e68355

DOI: 10.2196/68355

PMID: 40273403

PMCID: 12045519

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