R01AI151056
Project Grant
Overview
Grant Description
Improving Response to Malaria Outbreaks in Amazon-Basin Countries - Abstract
The objective of this proposal is to improve malaria response in the Amazon by enhancing knowledge on when, where, and which targeted interventions will have the greatest impact.
There is a critical need for improved malaria control—since 2011, no region in the world has experienced a larger increase in malaria than the Amazon. Several events contributed to this rise: extreme weather (i.e., El Nino), expanded resource extraction, political unrest in Venezuela, and withdrawal of the Global Fund from South America. The unprecedented malaria resurgence has been particularly high near border regions where migration and poor healthcare facilitate transmission.
The current surveillance system has a 4-week delay in cases reported, which is completely inadequate, resulting in reactive vs. preventive intervention strategies. To respond, our team developed a Malaria Early Warning System (MEWS) with NASA support for Loreto, Peru, where over 90% of malaria cases in Peru occur. The MEWS forecasts outbreaks with >90% sensitivity and >75% specificity 8-12 weeks in advance in sub-regions (ecoregions using unobserved component models [UCM]) and districts (via spatial Bayesian models), and fits community-based agent-based models (ABMs) to evaluate behavioral factors associated with transmission.
However, gaps remain: our MEWS has unknown performance outside of Peru; it does not incorporate migration; forecasts are not downscaled for hotspot detection; forecasting performance is poor near border regions; and the models are not integrated across scales.
We address these gaps with three aims: (1) evaluate MEWS expansion to the Ecuadorian and Brazilian Amazon and evaluate sub-district downscaled forecasts; (2) evaluate the relationship between infrastructure, socioeconomic networks, and migration across international borders with malaria incidence; and (3) evaluate scenarios of potential malaria interventions along borders to reduce malaria risk in both countries using ABMs.
This project will significantly improve current surveillance efforts by providing both current estimates and forecasts of malaria using state-of-the-art climate, hydrology, and land cover models. The MEWS is expanded by obtaining surveillance and population data from Ecuador and Brazil, and merging these with hydro-meteorological data. New ecoregions that ignore administrative borders are defined and UCMs are applied. Spatial Bayesian models are used to estimate both district- and downscaled sub-district level malaria incidence.
Infrastructure data are obtained from public sources and a social network analysis (and data collection) will be conducted in communities along border regions (Brazil-Peru, Ecuador-Peru). We evaluate malaria incidence along identified network structures up to 300km away from borders and test simulated intervention scenarios in border communities to evaluate effects on malaria transmission.
This proposal responds to the WHO 2016-2030 Global Technical Strategy for Malaria and the recent initiatives by the Pan American Health Organization calling for improved malaria surveillance as a core intervention to improve response to high malaria burden.
The objective of this proposal is to improve malaria response in the Amazon by enhancing knowledge on when, where, and which targeted interventions will have the greatest impact.
There is a critical need for improved malaria control—since 2011, no region in the world has experienced a larger increase in malaria than the Amazon. Several events contributed to this rise: extreme weather (i.e., El Nino), expanded resource extraction, political unrest in Venezuela, and withdrawal of the Global Fund from South America. The unprecedented malaria resurgence has been particularly high near border regions where migration and poor healthcare facilitate transmission.
The current surveillance system has a 4-week delay in cases reported, which is completely inadequate, resulting in reactive vs. preventive intervention strategies. To respond, our team developed a Malaria Early Warning System (MEWS) with NASA support for Loreto, Peru, where over 90% of malaria cases in Peru occur. The MEWS forecasts outbreaks with >90% sensitivity and >75% specificity 8-12 weeks in advance in sub-regions (ecoregions using unobserved component models [UCM]) and districts (via spatial Bayesian models), and fits community-based agent-based models (ABMs) to evaluate behavioral factors associated with transmission.
However, gaps remain: our MEWS has unknown performance outside of Peru; it does not incorporate migration; forecasts are not downscaled for hotspot detection; forecasting performance is poor near border regions; and the models are not integrated across scales.
We address these gaps with three aims: (1) evaluate MEWS expansion to the Ecuadorian and Brazilian Amazon and evaluate sub-district downscaled forecasts; (2) evaluate the relationship between infrastructure, socioeconomic networks, and migration across international borders with malaria incidence; and (3) evaluate scenarios of potential malaria interventions along borders to reduce malaria risk in both countries using ABMs.
This project will significantly improve current surveillance efforts by providing both current estimates and forecasts of malaria using state-of-the-art climate, hydrology, and land cover models. The MEWS is expanded by obtaining surveillance and population data from Ecuador and Brazil, and merging these with hydro-meteorological data. New ecoregions that ignore administrative borders are defined and UCMs are applied. Spatial Bayesian models are used to estimate both district- and downscaled sub-district level malaria incidence.
Infrastructure data are obtained from public sources and a social network analysis (and data collection) will be conducted in communities along border regions (Brazil-Peru, Ecuador-Peru). We evaluate malaria incidence along identified network structures up to 300km away from borders and test simulated intervention scenarios in border communities to evaluate effects on malaria transmission.
This proposal responds to the WHO 2016-2030 Global Technical Strategy for Malaria and the recent initiatives by the Pan American Health Organization calling for improved malaria surveillance as a core intervention to improve response to high malaria burden.
Awardee
Funding Goals
TO ASSIST PUBLIC AND PRIVATE NONPROFIT INSTITUTIONS AND INDIVIDUALS TO ESTABLISH, EXPAND AND IMPROVE BIOMEDICAL RESEARCH AND RESEARCH TRAINING IN INFECTIOUS DISEASES AND RELATED AREAS, TO CONDUCT DEVELOPMENTAL RESEARCH, TO PRODUCE AND TEST RESEARCH MATERIALS. TO ASSIST PUBLIC, PRIVATE AND COMMERCIAL INSTITUTIONS TO CONDUCT DEVELOPMENTAL RESEARCH, TO PRODUCE AND TEST RESEARCH MATERIALS, TO PROVIDE RESEARCH SERVICES AS REQUIRED BY THE AGENCY FOR PROGRAMS IN INFECTIOUS DISEASES, AND CONTROLLING DISEASE CAUSED BY INFECTIOUS OR PARASITIC AGENTS, ALLERGIC AND IMMUNOLOGIC DISEASES AND RELATED AREAS. PROJECTS RANGE FROM STUDIES OF MICROBIAL PHYSIOLOGY AND ANTIGENIC STRUCTURE TO COLLABORATIVE TRIALS OF EXPERIMENTAL DRUGS AND VACCINES, MECHANISMS OF RESISTANCE TO ANTIBIOTICS AS WELL AS RESEARCH DEALING WITH EPIDEMIOLOGICAL OBSERVATIONS IN HOSPITALIZED PATIENTS OR COMMUNITY POPULATIONS AND PROGRESS IN ALLERGIC AND IMMUNOLOGIC DISEASES. BECAUSE OF THIS DUAL FOCUS, THE PROGRAM ENCOMPASSES BOTH BASIC RESEARCH AND CLINICAL RESEARCH. SMALL BUSINESS INNOVATION RESEARCH (SBIR) PROGRAM EXPANDS AND IMPROVES PRIVATE SECTOR PARTICIPATION IN BIOMEDICAL RESEARCH. THE SBIR PROGRAM INTENDS TO INCREASE AND FACILITATE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT, TO INCREASE SMALL BUSINESS PARTICIPATION IN FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION OF SOCIALLY AND ECONOMICALLY DISADVANTAGED SMALL BUSINESS CONCERNS AND WOMEN-OWNED SMALL BUSINESS CONCERNS IN TECHNOLOGICAL INNOVATION. THE SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAM STIMULATES AND FOSTERS SCIENTIFIC AND TECHNOLOGICAL INNOVATION THROUGH COOPERATIVE RESEARCH AND DEVELOPMENT CARRIED OUT BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO FOSTER TECHNOLOGY TRANSFER BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION OF SOCIALLY AND ECONOMICALLY DISADVANTAGED SMALL BUSINESS CONCERNS AND WOMEN-OWNED SMALL BUSINESS CONCERNS IN TECHNOLOGICAL INNOVATION. RESEARCH CAREER DEVELOPMENT AWARDS SUPPORT THE DEVELOPMENT OF SCIENTISTS DURING THE FORMATIVE STAGES OF THEIR CAREERS. INDIVIDUAL NATIONAL RESEARCH SERVICE AWARDS (NRSAS) ARE MADE DIRECTLY TO APPROVE APPLICANTS FOR RESEARCH TRAINING IN SPECIFIED BIOMEDICAL SHORTAGE AREAS. IN ADDITION, INSTITUTIONAL NATIONAL RESEARCH SERVICE AWARDS ARE MADE TO ENABLE INSTITUTIONS TO SELECT AND MAKE AWARDS TO INDIVIDUALS TO RECEIVE TRAINING UNDER THE AEGIS OF THEIR INSTITUTIONAL PROGRAM.
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Durham,
North Carolina
27705
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 364% from $727,906 to $3,375,825.
Duke University was awarded
Amazon Malaria Response Enhancement Grant
Project Grant R01AI151056
worth $3,375,825
from the National Institute of Allergy and Infectious Diseases in September 2021 with work to be completed primarily in Durham North Carolina United States.
The grant
has a duration of 5 years and
was awarded through assistance program 93.855 Allergy and Infectious Diseases Research.
The Project Grant was awarded through grant opportunity Research Project Grant (Parent R01 Clinical Trial Not Allowed).
Status
(Ongoing)
Last Modified 9/24/25
Period of Performance
9/1/21
Start Date
8/31/26
End Date
Funding Split
$3.4M
Federal Obligation
$0.0
Non-Federal Obligation
$3.4M
Total Obligated
Activity Timeline
Transaction History
Modifications to R01AI151056
Additional Detail
Award ID FAIN
R01AI151056
SAI Number
R01AI151056-2923921196
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Private Institution Of Higher Education
Awarding Office
75NM00 NIH National Institute of Allergy and Infectious Diseases
Funding Office
75NM00 NIH National Institute of Allergy and Infectious Diseases
Awardee UEI
TP7EK8DZV6N5
Awardee CAGE
4B478
Performance District
NC-04
Senators
Thom Tillis
Ted Budd
Ted Budd
Budget Funding
Federal Account | Budget Subfunction | Object Class | Total | Percentage |
---|---|---|---|---|
National Institute of Allergy and Infectious Diseases, National Institutes of Health, Health and Human Services (075-0885) | Health research and training | Grants, subsidies, and contributions (41.0) | $1,268,510 | 100% |
Modified: 9/24/25