Identification of suspected paragonimiasis-endemic foci using a questionnaire and detection of Paragonimus ova using the Ziehl-Neelsen technique in Zamboanga Region, the Philippines.

Improving paragonimiasis surveillance, which is crucial for disease control, requires adopting new tools and techniques useful in mapping endemic areas. This study aimed to (1) develop a questionnaire to identify suspected paragonimiasis-endemic foci, (2) describe the epidemiology of paragonimiasis, and (3) evaluate Ziehl-Nielsen Staining technique (ZNS) in detecting Paragonimus ova. The questionnaire, which municipal health officers filled out, was based on proposed site inclusion criteria utilized in the integrated tuberculosis (TB)-paragonimiasis surveillance and control project. Newly deployed medical technologists in Zamboanga Region underwent training, which included laboratory diagnosis of paragonimiasis using preserved and fresh specimens and an integrated tuberculosis-paragonimiasis survey in nine selected barangays (villages). Paragonimiasis cases were found in seven out of the nine barangays identified by the questionnaire. Of the 373 patients, three (0.80%) were TB-positive, and 29 (7.77%) were paragonimiasis-positive. The highest paragonimiasis prevalence (27%) was found in Barangay Libato. Ziehl-Neelsen Staining technique (ZNS) correctly detected 8 out of the 29 samples positive (sensitivity - 27.59%; 95% CI: 12.73-47.24%) and all the 334 samples negative (specificity - 100%; 95% CI: 98.90-100%) for Paragonimus ova. The questionnaire may be improved by refining the inclusion criteria. In paragonimiasis-endemic areas, the ZNS and the NaOH concentration technique may be used for detecting Paragonimus ova. Modifying the ZNS, for instance by including a concentration step, may improve its sensitivity. The model for the integrated capacity building of health workers and surveillance and research demonstrated in this project may contribute to improving surveillance and control of paragonimiasis and other neglected tropical diseases.