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General

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

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

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:

Data

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

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: