# Submicroscopic Burden of Zoonotic Plasmodium knowlesi Malaria on Mursala Island and Plasmodium falciparum and Plasmodium vivax Transmission in Mainland North Sumatra, Indonesia

## TL;DR

This study finds that zoonotic malaria caused by Plasmodium knowlesi is rare in North Sumatra but can lead to severe cases, highlighting the need for molecular testing.

## Contribution

The study uses ultrasensitive PCR to detect submicroscopic zoonotic malaria in Indonesia, revealing low transmission of Plasmodium knowlesi.

## Key findings

- 7 out of 64 participants on Mursala Island had Plasmodium knowlesi infections, undetected by microscopy.
- No Plasmodium knowlesi infections were found among 947 mainland participants.
- Molecular diagnostics are essential for identifying submicroscopic zoonotic malaria cases.

## Abstract

Accurate molecular tools are essential for estimating zoonotic malaria transmission in Southeast Asia. This study applied ultrasensitive reverse-transcriptase real-time polymerase chain reaction (PCR) to detect zoonotic malaria in febrile patients from health facilities across three mainland districts (Batubara, Tanjung Balai, and Central Tapanuli) and separately on Mursala Island, North Sumatra, Indonesia. Among 64 participants on Mursala, 7 (10.9%) adults had Plasmodium knowlesi infections (including 5 agricultural workers and 2 adults with severe WHO anemia), and 2 (3.1%) adults had Plasmodium vivax infections. All were negative by microscopy and panparasite lactate dehydrogenase rapid diagnostic tests. No P. knowlesi infections were identified among 947 participants from mainland sites; PCR detected confirmed Plasmodium species in 26%, including P. vivax (17.5%) and Plasmodium falciparum (7.5%), with 30% of cases being submicroscopic. No Plasmodium cynomolgi infections were identified. Plasmodium knowlesi transmission is low in North Sumatra; however, it may cause WHO-defined severe malaria. Molecular diagnostics remain crucial for identifying zoonotic malaria and should be integrated into surveillance systems to inform public health control measures.