New app recommends strategies for integrating disease control programs

Photo of Claire Standley
Claire J. Standley

Researchers at Georgetown University have developed a web-based application that allows public health officials and policymakers to make decisions about integrating disease control programs in their communities.

The app, now available online, uses local information such as population demographics, disease incidence and transmission patterns to make recommendations on which interventions, if any, should be implemented, according to Claire J. Standley, PhD, MSc, assistant research professor at the Center for Global Health Science and Security at Georgetown University, and colleagues.

“Our work aims to highlight opportunities for innovative approaches to disease integration, with an emphasis on getting the best available evidence in the hands of decision-makers on the ground,” Standley told Infectious Disease News.

The researchers demonstrated the functionality of the app in a study recently published in PLoS Neglected Tropical Diseases. They used data from sub-Saharan Africa and the Middle East to predict whether integrating disease control programs for malaria and schistosomiasis, which are coendemic in the regions, is beneficial.

“While we focused initially on schistosomiasis and malaria as a proof-of-principle, the approach could similarly be applied to other diseases or public health issues, as a means of optimizing resource allocation and epidemiological outcomes,” Standley said.

The app based its recommendations on disease integration programs using fixed parameters that reflect academic literature, as well as user inputs on local conditions, such as age population distribution, resource availability and seasonal disease transmission rates. It decided the appropriateness of implementing various interventions, including insecticide-treated bed nets and indoor residual insecticide spraying for malaria, as well as mass drug administration of praziquantel for schistosomiasis. The results are presented on a single page that contains information on which interventions should be implemented and for how long.

Research partners who used the app in Mali, Uganda and Yemen provided positive feedback, confirming its feasibility and value in public health decision-making, according to the researchers. Standley and colleagues said they will work to expand the app’s functionality to take into account communities’ logistical issues with resource allocations.

“In this era of increasingly constrained resources for global health, our approach provides an opportunity to link epidemiological evidence with intervention costs, to optimize delivery of health services and effectiveness of control programming,” Standley and colleagues concluded. – by Stephanie Viguers

For more information:

Georgetown University. Integrated Control of NTDs. http://integratedntd.talusanalytics.com/#. Accessed April 13, 2018.

Standley CJ, et al. PLoS Negl Trop Dis. 2018;doi:10.1371/journal.pntd.0006328.

Disclosures: Standley reports no relevant financial disclosures. Please see the study for all other authors’ relevant financial disclosures.

Photo of Claire Standley
Claire J. Standley

Researchers at Georgetown University have developed a web-based application that allows public health officials and policymakers to make decisions about integrating disease control programs in their communities.

The app, now available online, uses local information such as population demographics, disease incidence and transmission patterns to make recommendations on which interventions, if any, should be implemented, according to Claire J. Standley, PhD, MSc, assistant research professor at the Center for Global Health Science and Security at Georgetown University, and colleagues.

“Our work aims to highlight opportunities for innovative approaches to disease integration, with an emphasis on getting the best available evidence in the hands of decision-makers on the ground,” Standley told Infectious Disease News.

The researchers demonstrated the functionality of the app in a study recently published in PLoS Neglected Tropical Diseases. They used data from sub-Saharan Africa and the Middle East to predict whether integrating disease control programs for malaria and schistosomiasis, which are coendemic in the regions, is beneficial.

“While we focused initially on schistosomiasis and malaria as a proof-of-principle, the approach could similarly be applied to other diseases or public health issues, as a means of optimizing resource allocation and epidemiological outcomes,” Standley said.

The app based its recommendations on disease integration programs using fixed parameters that reflect academic literature, as well as user inputs on local conditions, such as age population distribution, resource availability and seasonal disease transmission rates. It decided the appropriateness of implementing various interventions, including insecticide-treated bed nets and indoor residual insecticide spraying for malaria, as well as mass drug administration of praziquantel for schistosomiasis. The results are presented on a single page that contains information on which interventions should be implemented and for how long.

Research partners who used the app in Mali, Uganda and Yemen provided positive feedback, confirming its feasibility and value in public health decision-making, according to the researchers. Standley and colleagues said they will work to expand the app’s functionality to take into account communities’ logistical issues with resource allocations.

“In this era of increasingly constrained resources for global health, our approach provides an opportunity to link epidemiological evidence with intervention costs, to optimize delivery of health services and effectiveness of control programming,” Standley and colleagues concluded. – by Stephanie Viguers

For more information:

Georgetown University. Integrated Control of NTDs. http://integratedntd.talusanalytics.com/#. Accessed April 13, 2018.

Standley CJ, et al. PLoS Negl Trop Dis. 2018;doi:10.1371/journal.pntd.0006328.

Disclosures: Standley reports no relevant financial disclosures. Please see the study for all other authors’ relevant financial disclosures.