Laboratory #Diagnosis of #Hendra and #Nipah: Two Emerging Zoonotic Diseases with One Health Significance

Abstract

Hendra virus (HeV) and Nipah virus (NiV) are two highly pathogenic RNA viruses with zoonotic potential, which can cause severe diseases with high mortality rates (50–100%) in humans and animals. Given this context, these viruses are classified as Biosafety Level 4 (BSL-4) pathogens, thus limiting research studies. Despite the high case fatalities, there are currently no human vaccines available for either virus, owing in part to the limitations in research and hesitancy in funding. In the absence of widespread vaccination, diagnostic tests are crucial for the rapid identification of cases and disease surveillance. This review synthesizes current knowledge on the epidemiology, transmission dynamics, and pathogenesis of NiV and HeV to contextualize a detailed assessment of the available diagnostic tools. We examined molecular and serological assays, including RT-PCR, ELISA, and LAMP, highlighting sample sources, detection windows, and performance. Diagnostic considerations across human and animal hosts are discussed, with emphasis on outbreak applicability and field-readiness, given the need for diagnostic assays that are suitable for use in low-income areas. Further development of diagnostic assays, including isothermal amplification tests and other next-generation approaches, is recommended to fill the gap in rapid, point-of-care diagnostics.

Source: Viruses, https://www.mdpi.com/1999-4915/17/7/1003

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Modeling Effects of Routine #Screening for Accidental #Lab-Acquired #Infections on #Risk of Potential #Pandemic Pathogen #Escape from High-Biosafety Research Facilities

Abstract

Accidental lab–acquired infections (LAIs) risk releasing potential pandemic pathogens (PPPs) from BSL–3/4 facilities. We constructed a stochastic network infectious disease model to simulate how the probability of an outbreak of a pathogen resembling wild–type SARS–COV–2, following an initial LAI would be influenced by test–and–isolate interventions over a 100–day horizon. We varied test frequency (0–7 tests/week), peak sensitivity (50–100%), and isolation delay (0–3 days). For each of 192 parameter combinations, we conducted 1,000 simulations and used logistic regression to quantify how each parameter influenced the likelihood of an outbreak of 50 or more infections. Results indicated that even relatively infrequent routine testing significantly reduced the risk of outbreaks under diverse plausible scenarios, with greater reductions achieved at higher test frequencies. Once-weekly testing reduced outbreak risk by 52% under optimistic assumptions (80% sensitivity, 1–day delay) and by 29% under pessimistic assumptions (50% sensitivity, 2–day delay). Testing two and five times weekly yielded risk reductions of up to 62% and 71%, respectively, under optimistic assumptions, and 43% and 55%, respectively, under pessimistic assumptions. Logistic regression showed each additional weekly test decreased outbreak odds by 20%, each 10–point increase in test sensitivity reduced odds by 10%, and each additional isolation delay day increased odds by 15.5%. Interaction analyses revealed that longer isolation delays attenuated the protective effects of higher testing frequency and sensitivity. Routine lab worker screening with prompt isolation substantially mitigates PPP escape risks. High–frequency testing has the greatest impact, and policymakers should consider implementing regular screening protocols.

Source: MedRxIV, https://www.medrxiv.org/content/10.1101/2025.05.16.25327796v1

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