Forecasting Trachoma Control

NIH RePORTER · NIH · R01 · $403,750 · view on reporter.nih.gov ↗

Abstract

PROJECT SUMMARY/ABSTRACT Trachoma programs have been enormously successful, but they fell short of their goal of Global Elimination of Trachoma by 2020. Nearly one third of endemic districts still had not met the threshold for control. Why? One reason may be that the 2020 goals were set long before sufficient evidence was available. In the original grant period, we used program surveys to forecast the distribution of active trachoma worldwide. We also used NEI clinical trial data to better define the relationship between clinical activity and actual chlamydial infection. New clinical, infection, and serology data will now enable more precise estimates. In carrying out the aims of this current proposal, we will use these enriched information sources to forecast which districts will achieve control under current efforts. A second factor is that the trachoma intervention guidelines have essentially been “one size fits all”. Here, we propose to assess the enhanced interventions necessary to achieve control in hotspots where current efforts are not sufficient for trachoma control. Finally, the WHO plan acknowledged that resurgence may happen. In the original grant period, we demonstrated that surveys of trachoma prevalence sometimes switched from supporting control to questioning control. In this current proposal we propose to model resurgence so that surveillance of resurgence can be improved. In summary, we propose: (a) real-time open-access forecasts that set realistic interim and elimination goals to help keep our specific collaborating stakeholder's programs on track; (b) models for better targeting hot spots with enhanced interventions to accelerate success; (c) models for rational surveillance for resurgence to maintain control once success has been declared.

Key facts

NIH application ID
10587368
Project number
2R01EY025350-05A1
Recipient
UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
Principal Investigator
THOMAS M LIETMAN
Activity code
R01
Funding institute
NIH
Fiscal year
2023
Award amount
$403,750
Award type
2
Project period
2016-06-01 → 2028-05-31