Study Overview
- Title:
- Does deforestation increase malaria prevalence? Evidence from satellite data and health surveys (pre-analysis plan 1 of 2: Liberia only)
- Study is 3ie funded:
- No
- Study ID:
- RIDIE-STUDY-ID-5b7a6687cb876
- Initial Registration Date:
- 09/22/2017
- Last Update Date:
- 08/20/2018
- Study Status:
- Completed
- Location(s):
- Liberia
- Abstract:
Malaria remains a substantial health burden in many countries. Pathways through which deforestation has been found to increase malaria risk include forest-cover effects, forest-cover-loss effects, and socio-economic associations. A growing number of studies have examined whether deforestation increases malaria prevalence in humans, with the majority of these analyses concluding that it does. But these studies have been based on a small number of countries using less-than-ideal forest data at the aggregate jurisdictional level. In this paper we combine fourteen years of 30-meter resolution satellite data on forest loss with tens of thousands of surveys of malaria and fever in children in more than 30 countries. Based on methods pre-specified in a pre-analysis plan, we test the ex-ante hypotheses that forest-cover loss increases malaria prevalence and that intermediate levels of forest cover have highest malaria prevalence. We further test ex ante hypotheses related to disaggregations; i.e., that the forest-cover-loss effect is greater in Latin America and Africa than Asia, greater at earlier stages of a forest transition, and greater for smaller cuts.
- Registration Citation:
Busch, J. and Bauhoff, S., 2017. Does deforestation increase malaria prevalence? Evidence from satellite data and health surveys (pre-analysis plan 1 of 2: Liberia only). Registry for International Development for Impact Evaluations (RIDIE). Available at: 10.23846/ridie119
- Categories:
- Agriculture and Rural Development
Environment and Disaster Management
Health, Nutrition, and Population
Multisector
- Additional Keywords:
- Cost-effectiveness analysis; Demographic and Health Surveys; Mediation Analysis
- Secondary ID Number(s):
Principal Investigator(s)
- Name of First PI:
- Jonah Busch
- Affiliation:
- Center for Global Development
- Name of Second PI:
- Sebastian Bauhoff
- Affiliation:
- Center for Global Development
Study Sponsor
- Name:
- Norwegian Agency for Development Cooperation
- Study Sponsor Location:
- Norway
Research Partner
- Name of Partner Institution:
- Type of Organization:
- Location:
Intervention Overview
- Intervention:
Deforestation. i.e., forest-cover loss as identified in Hansen et al 2013 at a forest cover threshold of 25% canopy cover.
- Private Intervention Details:
- Theory of Change:
- Multiple Treatment Arms Evaluated?
- Yes
Implementing Agency
- Name of Organization:
- n/a
- Type of Organization:
- Other
Program Funder
- Name of Organization:
- n/a
- Type of Organization:
- Other
Intervention Timing
- Intervention or Program Started at time of Registration?
- Yes
- Start Date:
- 01/01/2000
- End Date:
Evaluation Method Overview
- Primary (or First) Evaluation Method:
- Regression with controls
- Other (not Listed) Method:
- Additional Evaluation Method (If Any):
- Difference in difference/fixed effects
- Other (not Listed) Method:
Method Details
- Details of Evaluation Approach:
Full outline of methods appended.
- Private Details of Evaluation Approach:
- Outcomes (Endpoints):
Outcome variable (1): malaria in children under 5 (rapid test) Outcome variable (2): malaria in children under 5 (microscopy) Outcome variable (3): fever in children under 5
- Unit of Analysis:
- Child under the age of 5
- Hypotheses:
Primary hypotheses: • Deforestation increases malaria prevalence, ceteris paribus • Deforestation increases fever prevalence, ceteris paribus We examine three pre-specified disaggregations, with ex ante hypotheses derived from published literature: • Continent – Deforestation hypothesized to increase malaria and fever prevalence more in Africa and Latin America than Asia, ceteris paribus • Forest transition - Deforestation hypothesized to increase malaria and fever prevalence more at higher levels of forest cover, ceteris paribus • Clearing size - Deforestation hypothesized to increase malaria and fever prevalence more for smaller clearings, ceteris paribus
- Unit of Intervention or Assignment:
- ~5.5x5.5 km cell
- Number of Clusters in Sample:
- In the Liberia analysis, thousands of cells. In the full study, hundreds of thousands of cells.
- Number of Individuals in Sample:
- Thousands.
- Size of Treatment, Control, or Comparison Subsamples:
- Of the thousands of surveyed children, some fraction will be in cell-years with non-zero (positive) deforestation. We do not know in advance what this fraction is.
Supplementary Files
- Analysis Plan:
- Outline for pre-analysis plan_LIBERIA FINAL_29 Aug 2017.docx
- Other Documents:
Outcomes Data
- Description:
- Demographic and Health Survey results of malaria and fever in children under 5.
- Data Already Collected?
- Yes
- Data Previously Used?
- Yes
- Data Access:
- Not restricted - access with no requirements or minimal requirements (e.g. web registration)
- Data Obtained by the Study Researchers?
- Yes
- Data Approval Process:
- Approval Status:
Treatment Assignment Data
- Participation or Assignment Information:
- No
- Description:
- Tree cover and tree cover loss. Hansen et al, Science, 2013. Forest threshold=25%. Gridded to ~5.5 km x 5.5 km cells by Jens Engelmann as described in Busch and Engelmann 2014.
- Data Obtained by the Study Researchers?
- Yes
- Data Previously Used?
- Yes
- Data Access:
- Not restricted - access with no requirements or minimal requirements (e.g. web registration)
- Data Obtained by the Study Researchers?
- Yes
- Data Approval Process:
- Approval Status:
Data Analysis
- Data Analysis Status:
- No
Study Materials
- Upload Study Materials:
Registration Category
- Registration Category:
- Prospective, Category 3: Data for measuring impacts have been obtained/collected by the research team but analysis for this evaluation has not started
Completion Overview
- Intervention Completion Date:
- Data Collection Completion Date:
- Unit of Analysis:
- Clusters in Final Sample:
- Total Observations in Final Sample:
- Size of Treatment, Control, or Comparison Subsamples:
Findings
- Preliminary Report:
- Preliminary Report URL:
- Summary of Findings:
- Paper:
- Paper Summary:
- Paper Citation:
Data Availability
- Data Availability (Primary Data):
- Date of Data Availability:
- Data URL or Contact:
- Access procedure:
Other Materials
- Survey:
- Survey Instrument Links or Contact:
- Program Files:
- Program Files Links or Contact:
- External Link:
- External Link Description:
- Description of Changes:
Study Stopped
- Date:
- Reason: