Tropical Health Matters

World Malaria Day 2014 was observed at the Johns Hopkins Bloomberg School of Public Health on Friday 25 April. 21 posters were presented. Below is the abstract of a poster presented by Antonio M. Quispe (aquispe@jhu.edu) and Josiah L. Kephart of the U.S. Naval Medical Research Unit Six (NAMRU-6), Lima, Peru and Johns Hopkins Bloomberg School of Public Health, Baltimore.

After a decade of decline, malaria prevalence in the Peruvian Amazon quadrupled from 2010 to 2013.(1) The most plausible explanation for this reemergence is administrative, as a concurrent dengue outbreak has forced authorities to reallocate their resources away from malaria and towards dengue. The current surveillance system provides epidemiological analysis on a macro level only, limiting decision-makers ability to efficiently distribute resources towards both diseases simultaneously by targeting outbreaks on a micro level and in a timely manner.

We have developed the Free Surveillance Application (FREESAPP), an online application that facilitates epidemiologic analysis and cost-effectiveness decision trees using data already collected by the malaria surveillance system. By leveraging free and publicly available software (Google Docs, R, etc.), the app provides public health decision-makers with the ability to transform weekly epidemiological reports into exploratory analysis, monitor epidemiologic thresholds, and assess the cost-effectiveness of deploying various control methods.

FREESAPP enables users to visually contrast malaria incidence rates with   epidemiological thresholds. When the weekly epidemiologic report is uploaded, the visualization will automatically update, providing a signi?cant time-advantage over the current system of annual   reporting. These comparisons can be also performed across reporting levels, from the regional   to individual health center levels (Fig 1).

The app facilitates follow-up analysis through the ability to combine or adjust for various relevant covariates (incident rate, population size, P. vivax proportion, time, etc.) using several display options (bubble, bar, and line charts) and offering a variety of mathematical transformations (linear and logarithmic) (Fig 2).

FREESAPP allows decision makers to get a sense of the relative costs of deploying a team of health workers to perform either active case detection (ACD) or reactive case detection (RCD) in responses to an outbreak or malaria elimination effort within a particular community. ACD targets the malaria burden (symptomatic cases only) by searching for malaria cases among the entire population at risk, while RCD targets the malaria reservoir (both symptomatic and asymptomatic cases) by focusing on malaria infections within high-risk sub-populations.(2) To compare these methods, we have developed a decision tree that assists in the decision-making process of the optimal strategy for outbreak responses and malaria elimination initiatives, adapting the model developed by Shillcut et al.(3)

By utilizing publicly available software, FREESAPP can provide public health decision-makers with valuable insight into malaria outbreaks and cost-efficient responses. Present malaria and dengue control efforts in Peru are limited by a lack of access to timely epidemiological analysis across all health-system levels. FREESAPP offers valuable and accessible tools to improve public health leaders’ ability to leverage data from existing surveillance systems of malaria and other infectious diseases to implement efficient and effective interventions.

References

1. WHO. Global Malaria Report 2013. Geneva: World Health Organization, 2013.
2. Moonen B et al. Operational strategies to achieve and maintain malaria elimination. Lancet. 2010; 376(9752): 1592-603
3. Shillcutt S et al. Cost-effectiveness of malaria diagnostic methods in sub-Saharan Africa in an era of combination therapy. Bull World Health Organ. 2008;86(2):101?10

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