Conference Agenda

Helminth infections, particularly schistosomiasis and soil-transmitted helminthiases, impose a severe global health burden, infecting more than a quarter of the world population, with a disproportionate effect on those in extreme poverty. Current diagnostic tests for worm infections are neither sufficiently sensitive nor field-friendly for use in resource-limited or low-endemic settings, leading to underestimation of true infection rates. Ultrasensitive, field-friendly, low-cost point-of-care diagnostics are urgently needed to better control these diseases.
Our group has established a highly sensitive CRISPR-Cas12/13-based platform for femtogram-level nucleic acid detection of multiple helminth infections. We also developed portable, lyophilized one-pot CRISPR detection to enable field testing, reducing reliance on cold-chain transportation and making it easier to perform. To further address the DNA sample preparation bottleneck in field applications, we developed a rapid extraction method that yields high-quality DNA for use with our CRISPR-based schistosomiasis diagnostic tool. Our method is faster and supports scalable, cost-effective field screening, compared with conventional DNA extraction.
To demonstrate the clinical utility of this integrated system, we are currently validating the assay for helminth detection using a large cohort of human samples from Uganda. This scalable, field-deployable approach holds significant potential to advance global NTD control and surveillance efforts.

Giemsa-stained blood smear microscopy is the gold standard for detecting malaria parasites, but it is time-consuming and limited for storage and reference. To address this, we developed PlasmoCount, a deep learning tool for accurate, automated counting of intracellular parasites and digital archiving support. Principally, we have achieved a substantial reduction in PlasmoCount’s processing time allowing for evaluation of a single image in under 3 seconds (reduced from 40). In addition, we have updated the tool so that it can now detect blood-stage infections from multiple species of human-infective and experimental rodent-infective Plasmodium parasites. Combined with a suite of other updates, including advanced cell differentiation and use at different magnifications, these augmentations broaden the distribution of input data our model can accommodate and radically advance its speed whilst maintaining its high classification accuracy (99.8%). Finally, we provide an offline, on-device version of the standardised framework designed for smartphones, including iOS and Android operating systems. By making use of imported images or image capture via a smartphone camera, PlasmoCount 2.0 markedly improves malaria parasite smear-based detection and provides a reproducible means to assess parasite infections either in routine laboratory work or as a future aid in clinical or field diagnosis.

Countries close to malaria elimination are reporting significant resurgence following periods of declining prevalence. Reduced transmission decreases opportunities for genetic recombination and generates geographically isolated hotspots of infection, resulting in lower diversity and increased population structure. With reduced exposure, naturally acquired immunity wanes, potentially rendering human populations more susceptible to outbreaks. But paradoxically, many low-transmission countries also record high prevalence of asymptomatic infections. We hypothesised that these asymptomatic cases are associated with immunologically familiar, locally circulating strains whereas clinically infectious parasites are potentially imported. We analysed Plasmodium falciparum samples from a period of low transmission (2012) prior to resurgence (2016) in East Sepik, Papua New Guinea (PNG), and from a low-transmission setting with ongoing occupational exposure in Mondulkiri, Cambodia, by sequencing a validated genome-wide single nucleotide polymorphism (SNP) barcode and immune evasion antigen marker (varcode). Parasite lineages underlying clinical infections in PNG were clonal and distinct from circulating asymptomatic isolates, suggesting potential importation and outbreak caused by immunologically unfamiliar parasites. Infections in Cambodia however indicate a more complex dynamic between parasite strain and host factors. These results emphasise how surveillance reliant on just clinical infections inadequately reflects control success and must account for asymptomatic malaria for sustainable reduction and elimination.

Transmission is a basic aspect of intestinal parasite’s biology that is poorly understood for Dientamoeba fragilis. Early historical reports reflecting the absence of a cyst are often cited as a central argument in debates supporting the lack of a D. fragilis cyst. Despite D. fragilis cysts being described since Dobell’s original description, their existence is not universally accepted. Here, Dobell’s, Wenyon’s, and Hoare’s collection of historical faecal smears stored at the Natural History Museum (London), dating back to the 1890s and the early 1900s, were examined for forms consistent with modern descriptions of D. fragilis cysts, and an example was found in one slide. Such rare forms were also detected during examination of stained faecal smears archived in the parasite reference laboratory collection at the United States Centers for Disease Control and Prevention (CDC). Considering published literature on the subject of D. fragilis cysts and the broader picture of cyst formation across diverse members of Parabasalia, we recommended that future investigations on D. fragilis transmission consider mounting evidence for the role of a true cyst despite its rarity in human faecal specimens. The factors leading to cyst formation and further characteristics of this life cycle stage require further study.

Babesiosis, caused by intraerythrocytic parasites of the genus Babesia, is an emerging zoonotic threat with a global distribution. Babesiosis ranges from asymptomatic to fulminant disease occurring predominantly in immunocompromised hosts, with fatality rates up-to 20%. Diagnosis traditionally relies on microscopic examination of blood smears; however, up-to 20% of infections are sub‑microscopic, risking transmission via blood transfusion, organ transplantation, and the ixodid tick vector. While molecular and immunodiagnostic methods exhibit improved sensitivity, they are costly, time‑consuming, technically complex, and invasive. Near‑infrared spectroscopy (NIRS) utilises near-infrared electromagnetic energy (350–2500 nm) to generate spectral signatures reflective of specific chemical changes in a biological sample. When coupled with machine learning algorithms, diagnostic features can be extracted, allowing sample classification. NIRS has been successfully applied as a non-invasive malaria diagnostic in mice and humans; however analogous studies have not been performed with Babesia spp. This study evaluated the ability of NIRS to non-invasively detect B. microti in mice. The sensitivity and specificity of non-invasive detection was compared to invasive detection (blood spots). By situating NIRS alongside established molecular detection methods, our goal is to lay the groundwork for a rapid, reagent‑free diagnostic that complements existing assays while enabling non‑invasive babesiosis surveillance and enhanced donor screening.