Lingual palpation for porcine cysticercosis: a rapid epidemiological tool for estimating prevalence and community risk in Africa.

Helen L Guyatt,Eric M Fèvre

doi:10.1111/tmi.12760

Abstract

ObjectiveTo assess the association between the prevalence of tongue cyst‐positive and antigen‐positive pigs across different settings in Africa, to evaluate whether examining pigs for cysts could be used as a rapid surveillance tool for identifying geographical areas with a higher probability of high transmission of cysticercosis.MethodsPublished data were collated from 26 study sites across Africa that reported the prevalence of porcine cysticercosis by both lingual and serological examinations. The study sites were located in 10 countries across Africa.ResultsSeroprevalence rates ranged from 4% to 41%. Despite the varied study sites, the relationship between the two variables was highly consistent and suggests identification of tongue cysts may be useful for cysticercosis surveillance. We found that all areas with more than 10% of pigs having cysts in their tongues had at least 30% seroprevalence (PPV of 100%), although this cut‐off is less reliable at predicting that an area is of low transmission (NPV of 84%).ConclusionAssessing the prevalence of tongue cyst‐positive pigs is a potential rapid epidemiological tool for identifying areas at high risk of cysticercosis, although further refinement and validation is required using standardised data sets.

Highlights

The Food and Agriculture Organization (FAO) has identified cysticercosis as the most important foodborne parasite globally [1] and WHO is committed to rolling out control of this disease by 2020 [2]
The prevalence of tongue cyst-positive pigs was less than the prevalence of antigen-positive pigs, Prevalence of tongue cyst positive pigs (%)
Tongue cyst-positive rates >10% varied between 12% and 26%, and suggest that a prevalence >10% would indicate a seroprevalence in pigs of more than 30%, with a positive predictive value (PPV) of 100% (7/7)

Summary

Introduction

The Food and Agriculture Organization (FAO) has identified cysticercosis as the most important foodborne parasite globally [1] and WHO is committed to rolling out control of this disease by 2020 [2]. Within these, high- and low-risk areas need to be identified, especially given the knowledge that intensity of infection can vary spatially [3]. To undertake such largescale surveillance, a cheap, simple, and rapid tool for diagnosing community risk is needed. This could be similar to those that have been established and implemented for schistosomiasis and the soil-transmitted nematodes [4], where large volumes of data on low- and high-risk communities can be rapidly generated and used in targeting interventions at appropriate geographical areas

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Results

Discussion

Conclusion