Timothy John R. Dizon

Leptospirosis is a highly endemic neglected tropical disease in the Philippines, where conventional diagnostic methods such as the microscopic agglutination test (MAT) provide limited information on circulating Leptospira and are affected by serological cross-reactivity. This study evaluated the utility of shotgun metagenomic next-generation sequencing (mNGS) for pathogen detection and species-level characterization using 20 archived serum-derived total nucleic acid extracts collected from suspected leptospirosis cases. Samples were previously tested by quantitative real-time PCR (qPCR) and MAT, and sequenced using the Illumina MiSeq platform. Host-derived reads were removed using BWA and SAMtools prior to taxonomic profiling with KrakenUniq. Species-level Leptospira assignments were retained based on predefined KrakenUniq filtering criteria, including a minimum taxReads threshold and evidence of taxon-specific unique k-mers. Leptospira taxReads were detected in 58.8% (n=10/17) of qPCR-positive samples. Notably, mNGS detected pathogenic Leptospira in 60% (n=6/10) qPCR-positive but MAT-negative samples, demonstrating its potential to complement conventional serology for etiological characterization. MAT reactivity was predominantly against L. biflexa serovar Patoc (n=4/5), with one sample reacting to L. interrogans serovar Autumnalis in the MAT-positive samples. Meanwhile, mNGS identified a predominance of L. interrogans, with additional detection of L. borgpetersenii and L. kirschneri. The absence of detectable Leptospira in some qPCR-positive samples underscores the sensitivity limitations of mNGS in low-burden or archived samples. Overall, mNGS provided species-level information beyond conventional diagnostics and supports its potential application in Leptospira genomic surveillance in the Philippines. IMPACT STATEMENT: Leptospirosis remains an important public health concern in the Philippines, but genomic information on human Leptospira infections is limited. Shotgun metagenomic sequencing provided species-level information beyond routine qPCR and MAT. Leptospira interrogans predominated, alongside other pathogenic species. These findings establish an initial genomic baseline for Leptospira in Philippine clinical specimens and support future surveillance of strain and serovar diversity and transmission.

Leptospirosis remains a public health concern in the Philippines. Conventional diagnostic methods, including the microscopic agglutination test (MAT) and qPCR, are routinely used for outbreak response and surveillance. However, these methods often yield discordant results due to cross-reactivity, limited sensitivity, or lack of species-level resolution. To address these diagnostic gaps, this study optimized the Boonsilp 16S rRNA PCR assay and applied Sanger sequencing for accurate species identification of Leptospira in 92 archived DNA samples collected between 2018 and 2020. The sensitivity and specificity of the optimized assay were compared with those of MAT and qPCR. Species-level identification was confirmed via sequencing, and a phylogenetic tree was constructed. Among the 92 samples, 46 (50.0%) tested positive by qPCR, 39 (42.4%) by MAT, and 67 (72.8%) by at least one of the two methods. The optimized Boonsilp assay detected Leptospira in 23 samples (25.0%), of which 22 were also qPCR positive. Twenty-one samples were confirmed as L. interrogans, one as L. borgpetersenii, and one as an unclassified Leptospira species. One sample undetected by both MAT and qPCR tested positive using the optimized assay. Compared to the composite reference, the Boonsilp assay showed 32.8% sensitivity and 96.0% specificity. Phylogenetic analysis revealed multiple L. interrogans strains, including those closely related to reference sequences of Copenhageni, Manilae, and Canicola. While the optimized Boonsilp PCR assay demonstrates diagnostic value as an adjunct molecular tool to qPCR and MAT supporting species-level identification during outbreak surveillance, this warrants further validation in freshly isolated DNA samples.

Co-infection with multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, though rare, may have clinical and public health implications, including facilitating variant recombination. Early detection of co-infections is, therefore, crucial. In this study, we report two probable cases of co-infection identified during routine genomic surveillance. Initially suspected as cross-contamination due to the presence of private mutations and nucleotide mixtures flagged by Nextclade and bammix, the samples were re-extracted and re-sequenced after workspace decontamination, yet the anomalies persisted. To investigate further, we developed a bioinformatics pipeline (Katmon) incorporating various tools such as Freyja, with lineage abundance results that illustrated the presence of multiple variants, and VirStrain, which confirmed inconsistent lineage assignments. We also visualized the alternative allele fractions for each lineage-defining mutation and amplicon, showing evidence of two variants, Delta and Omicron, co-existing within a single amplicon. Amplicon sorting effectively separated reads corresponding to the two variants, and the resulting consensus sequences aligned with their respective lineage assignments. These findings suggest that the first sample, PH-RITM-1395, involved a Delta–Omicron co-infection, while the second sample, PH-RITM-4146, probably contains both a co-infection and a recombinant variant. To further support the second sample’s recombinant nature, we employed sc2rf, which identified Delta–Omicron breakpoints. Retrospective analysis of 1,078 samples from July 2021 to July 2022, encompassing the period of co-circulation of different variants in the Philippines, flagged four additional co-infection cases, including Delta–Omicron and Beta–Omicron, suggesting a lower bound co-infection prevalence of 0.27% and 0.19%, respectively. Furthermore, the pipeline was used to test previously identified co-infections of different variants from different countries. Our findings underscore the critical importance of real-time genomic surveillance and advanced bioinformatics pipelines in detecting SARS-CoV-2 co-infections and variant recombination.

Extreme weather events (EWEs) continue to threaten the health and well‐being of populations across the globe. However, risk from drought and floods is not evenly distributed spatially nor are all populations equally at risk for poor health outcomes. Globally, people living with HIV/AIDS (PLHIV) face a particular set of challenges with EWE exposure including increased susceptibility to disease progression from care disruptions and medication adherence, and general population concentration in areas where rainfall is both highly variable and key to economic well‐being. To mitigate the impacts of EWE exposure on PLHIV, it is necessary to understand the historical EWE exposure patterns at HIV care clinics. In this paper, we link open‐source measures of drought and flood events to clinic locations from the International epidemiology Databases to Evaluate AIDS (IeDEA) network, a longitudinal study of over 2 million people living with and at risk for HIV in 44 different countries around the globe enrolling in HIV care from 2006 to present. Using generalized additive models fit to clinic‐level drought and flood exposures, we show how exposures vary across and within countries, model each clinic's probability of exposure to a drought or flood to identify high‐risk areas, and describe how this historical exposure record could ultimately be used to identify at‐risk populations for a wide variety of study designs. While EWEs occurred at HIV care clinics around the globe, we found that clinic locations in Southern Africa are particularly vulnerable to flood and drought events as compared to other IeDEA clinic regions and locations.

The Omicron severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant led to a dramatic global epidemic wave following detection in South Africa in November 2021. The BA.1 Omicron lineage was dominant and responsible for most SARS-CoV-2 outbreaks in countries around the world during December 2021–January 2022, while other Omicron lineages, including BA.2, accounted for the minority of global isolates. Here, we describe the Omicron wave in the Philippines by analysing genomic data. Our results identify the presence of both BA.1 and BA.2 lineages in the Philippines in December 2021, before cases surged in January 2022. We infer that only the BA.2 lineage underwent sustained transmission in the country, with an estimated emergence around 18 November 2021 (95 per cent highest posterior density: 6–28 November), while despite multiple introductions, BA.1 transmission remained limited. These results suggest that the Philippines was one of the earliest areas affected by BA.2 and reiterate the importance of whole genome sequencing for monitoring outbreaks.

The Omicron SARS-CoV-2 variant led to a dramatic global epidemic wave following detection in South Africa in November, 2021. The Omicron lineage BA.1 was dominant and responsible for most domestic outbreaks during December 2021-January 2022, whilst other Omicron lineages including BA.2 accounted for the minority of global isolates. Here, we describe the Omicron wave in the Philippines by analysing genomic data. Our results identify the presence of both BA.1 and BA.2 lineages in the Philippines in December 2021, before cases surged in January 2022. We infer that only lineage BA.2 underwent sustained transmission in the country, with an estimated emergence around November 18th, 2021 [95% highest posterior density: November 6-28th], whilst despite multiple introductions BA.1 transmission remained limited. These results suggest the Philippines was one of the earliest areas affected by BA.2, and reiterate the importance of whole-genome sequencing for monitoring outbreaks.

Background: Despite the effort to eradicate rabies in the Philippines, human rabies cases have not decreased in the past decade. Rabid dogs pose the most significant hazard in the countries with the highest burden of rabies, and 70% rabies vaccine coverage is recommended for dogs in high-risk areas. Ascertaining the owned dog population and community knowledge on rabies can help improve vaccine coverage and information campaigns. Methodology/Principal findings: We conducted a cross-sectional survey in six randomly selected communities (five urban, one rural) in Central Luzon, Philippines. We first conducted the complete mapping of 9,173 households and then randomly selected 727 households. More than half (54.1%) of the households owned dogs (1.21 dogs/household). In the 727 households, we identified 878 owned dogs and 3256 humans. According to these results, the dog-to-human ratio was approximately 1:3.7. Only 8.8% of households reported a history of dog bite in 2019. Among dog-owning households, 31% reported that they allow their dogs to roam freely. Of the recorded dogs, 35.9% have never been vaccinated, and only 3.5% were spayed or castrated. Factors associated with lower rabies knowledge include (1) no education aOR: 0.30 (0.16–0.59), and (2) only primary school education aOR: 0.33 (0.22–0.49). In contrast, factors associated with higher knowledge include (1) owning a dog and not allowing them to roam freely aOR: 2.01 (1.41–2.87) and (2) owning a dog and allowing them to roam freely aOR: 1.84 (1.17–2.92), when compared to those with no dogs. Conclusions/Significance: We identified a larger dog population in the community than the usual estimates (1:10), suggesting that annual vaccine needs in the Philippines must be reassessed. Our survey shows a relatively good understanding of rabies; however, awareness of the concept of rabies as a disease, and how animals and humans can acquire it, is lacking.