"Smart markets": harnessing the potential of new technologies for endemic and emerging infectious disease surveillance in traditional food markets.

Emerging and endemic zoonotic diseases continue to threaten human and animal health, our social fabric, and the global economy. Zoonoses frequently emerge from congregate interfaces where multiple animal species and humans coexist, including farms and markets. Traditional food markets are widespread across the globe and create an interface where domestic and wild animals interact among themselves and with humans, increasing the risk of pathogen spillover. Despite decades of evidence linking markets to disease outbreaks across the world, there remains a striking lack of pathogen surveillance programs that can relay timely, cost-effective, and actionable information to decision-makers to protect human and animal health. However, the strategic incorporation of environmental surveillance systems in markets coupled with novel pathogen detection strategies can create an early warning system capable of alerting us to the risk of outbreaks before they happen. Here, we explore the concept of "smart" markets that utilize continuous surveillance systems to monitor the emergence of zoonotic pathogens with spillover potential.IMPORTANCEFast detection and rapid intervention are crucial to mitigate risks of pathogen emergence, spillover and spread-every second counts. However, comprehensive, active, longitudinal surveillance systems at high-risk interfaces that provide real-time data for action remain lacking. This paper proposes "smart market" systems harnessing cutting-edge tools and a range of sampling techniques, including wastewater and air collection, multiplex assays, and metagenomic sequencing. Coupled with robust response pathways, these systems could better enable Early Warning and bolster prevention efforts.

Australia as a global sink for the genetic diversity of avian influenza A virus.

Most of our understanding of the ecology and evolution of avian influenza A virus (AIV) in wild birds is derived from studies conducted in the northern hemisphere on waterfowl, with a substantial bias towards dabbling ducks. However, relevant environmental conditions and patterns of avian migration and reproduction are substantially different in the southern hemisphere. Through the sequencing and analysis of 333 unique AIV genomes collected from wild birds collected over 15 years we show that Australia is a global sink for AIV diversity and not integrally linked with the Eurasian gene pool. Rather, AIV are infrequently introduced to Australia, followed by decades of isolated circulation and eventual extinction. The number of co-circulating viral lineages varies per subtype. AIV haemagglutinin (HA) subtypes that are rarely identified at duck-centric study sites (H8-12) had more detected introductions and contemporary co-circulating lineages in Australia. Combined with a lack of duck migration beyond the Australian-Papuan region, these findings suggest introductions by long-distance migratory shorebirds. In addition, on the available data we found no evidence of directional or consistent patterns in virus movement across the Australian continent. This feature corresponds to patterns of bird movement, whereby waterfowl have nomadic and erratic rainfall-dependant distributions rather than consistent intra-continental migratory routes. Finally, we detected high levels of virus gene segment reassortment, with a high diversity of AIV genome constellations across years and locations. These data, in addition to those from other studies in Africa and South America, clearly show that patterns of AIV dynamics in the Southern Hemisphere are distinct from those in the temperate north.

"Hospitals respond to demand. Public health needs to respond to risk": health system lessons from a case study of northern Queensland's COVID-19 surveillance and response.

BACKGROUND: The vast region of northern Queensland (NQ) in Australia experiences poorer health outcomes and a disproportionate burden of communicable diseases compared with urban populations in Australia. This study examined the governance of COVID-19 surveillance and response in NQ to identify strengths and opportunities for improvement. METHODS: The manuscript presents an analysis of one case-unit within a broader case study project examining systems for surveillance and response for COVID-19 in NQ. Data were collected between October 2020-December 2021 comprising 47 interviews with clinical and public health staff, document review, and observation in organisational settings. Thematic analysis produced five key themes. RESULTS: Study findings highlight key strengths of the COVID-19 response, including rapid implementation of response measures, and the relative autonomy of NQ's Public Health Units to lead logistical decision-making. However, findings also highlight limitations and fragility of the public health system more generally, including unclear accountabilities, constraints on local community engagement, and workforce and other resourcing shortfalls. These were framed by state-wide regulatory and organisational incentives that prioritise clinical health care rather than disease prevention, health protection, and health promotion. Although NQ mobilised an effective COVID-19 response, findings suggest that NQ public health systems are marked by fragility, calling into question the region's preparedness for future pandemic events and other public health crises. CONCLUSIONS: Study findings highlight an urgent need to improve governance, resourcing, and political priority of public health in NQ to address unmet needs and ongoing threats.

Development of subfamily-based consensus PCR assays for the detection of human and animal herpesviruses.

Consensus PCR assays that can be used to sensitively detect several herpesvirus (HV) species across the different subfamilies were developed in this study. Primers containing degenerate bases were designed to amplify regions of the DNA polymerase (DPOL) gene of alpha- and gamma-HVs, and the glycoprotein B (gB) gene of beta-HVs in a singleplex, non-nested touchdown PCR format. The singleplex touchdown consensus PCR (STC-PCR) was used to amplify the DNA of eight human and 24 animal HVs. The assay was able to detect the lowest DNA dilution of 10-5 for alpha-HVs and 10-3 for beta- and gamma-HVs. In comparison, lowest detection limits of 10-5, 10-3, and 10-2 were obtained for alpha-, beta-, and gamma-HVs respectively when a nested PCR was used. The findings in this study suggest that the STC-PCR assays can be employed for the molecular surveys and clinical detection of novel and known HVs.

Zoonotic Pathogens in Wildlife Traded in Markets for Human Consumption, Laos.

We tested animals from wildlife trade sites in Laos for the presence of zoonotic pathogens. Leptospira spp. were the most frequently detected infectious agents, found in 20.1% of animals. Rickettsia typhi and R. felis were also detected. These findings suggest a substantial risk for exposure through handling and consumption of wild animal meat.

Quantifying within-host diversity of H5N1 influenza viruses in humans and poultry in Cambodia.

Avian influenza viruses (AIVs) periodically cross species barriers and infect humans. The likelihood that an AIV will evolve mammalian transmissibility depends on acquiring and selecting mutations during spillover, but data from natural infection is limited. We analyze deep sequencing data from infected humans and domestic ducks in Cambodia to examine how H5N1 viruses evolve during spillover. Overall, viral populations in both species are predominated by low-frequency (<10%) variation shaped by purifying selection and genetic drift, and half of the variants detected within-host are never detected on the H5N1 virus phylogeny. However, we do detect a subset of mutations linked to human receptor binding and replication (PB2 E627K, HA A150V, and HA Q238L) that arose in multiple, independent humans. PB2 E627K and HA A150V were also enriched along phylogenetic branches leading to human infections, suggesting that they are likely human-adaptive. Our data show that H5N1 viruses generate putative human-adapting mutations during natural spillover infection, many of which are detected at >5% frequency within-host. However, short infection times, genetic drift, and purifying selection likely restrict their ability to evolve extensively during a single infection. Applying evolutionary methods to sequence data, we reveal a detailed view of H5N1 virus adaptive potential, and develop a foundation for studying host-adaptation in other zoonotic viruses.

Divergent Barmah Forest Virus from Papua New Guinea.

We report a case of Barmah Forest virus infection in a child from Central Province, Papua New Guinea, who had no previous travel history. Genomic characterization of the virus showed divergent origin compared with viruses previously detected, supporting the hypothesis that the range of Barmah Forest virus extends beyond Australia.

Emergence of Influenza A(H7N4) Virus, Cambodia.

Active surveillance in high-risk sites in Cambodia has identified multiple low-pathogenicity influenza A(H7) viruses, mainly in ducks. None fall within the A/Anhui/1/2013(H7N9) lineage; however, some A(H7) viruses from 2018 show temporal and phylogenetic similarity to the H7N4 virus that caused a nonfatal infection in Jiangsu Province, China, in December 2017.

Inventory of molecular markers affecting biological characteristics of avian influenza A viruses.

Avian influenza viruses (AIVs) circulate globally, spilling over into domestic poultry and causing zoonotic infections in humans. Fortunately, AIVs are not yet capable of causing sustained human-to-human infection; however, AIVs are still a high risk as future pandemic strains, especially if they acquire further mutations that facilitate human infection and/or increase pathogenesis. Molecular characterization of sequencing data for known genetic markers associated with AIV adaptation, transmission, and antiviral resistance allows for fast, efficient assessment of AIV risk. Here we summarize and update the current knowledge on experimentally verified molecular markers involved in AIV pathogenicity, receptor binding, replicative capacity, and transmission in both poultry and mammals with a broad focus to include data available on other AIV subtypes outside of A/H5N1 and A/H7N9.

Co-circulation of Influenza A H5, H7, and H9 Viruses and Co-infected Poultry in Live Bird Markets, Cambodia.

Longitudinal surveillance of 2 live bird markets in Cambodia revealed year-round, high co-circulation of H5, H7, and H9 influenza viruses. We detected influenza A viruses in 51.3% of ducks and 39.6% of chickens, and co-infections, mainly by H5 and H9 viruses, in 0.8% of ducks and 4.5% of chickens.

Detection of Low Pathogenicity Influenza A(H7N3) Virus during Duck Mortality Event, Cambodia, 2017.

In January 2017, an estimated 3,700 (93%) of 4,000 Khaki Campbell ducks (Anas platyrhynchos domesticus) died in Kampong Thom Province, Cambodia. We detected low pathogenicity avian influenza A(H7N3) virus and anatid herpesvirus 1 (duck plague) in the affected flock; however, the exact cause of the mortality event remains unclear.

Low Circulation of Zika Virus, Cambodia, 2007-2016.

We describe a retrospective study on circulation of Zika virus in Cambodia during 2007-2016 among patients with dengue-like symptoms and Aedes aegypti mosquitoes. Our findings suggest that Zika virus in Cambodia belongs to the Asia genotype, is endemic, has low prevalence, and has had low-level impact on public health.

Seroepidemiology of Human Enterovirus 71 Infection among Children, Cambodia.

Enterovirus 71 is reported to have emerged in Cambodia in 2012; at least 54 children with severe encephalitis died during that outbreak. We used serum samples collected during 2000-2011 to show that the virus had been widespread in the country for at least a decade before the 2012 outbreak.

Association of protein intakes and variation of diet-scalp hair nitrogen isotopic discrimination factor in Papua New Guinea highlanders.

OBJECTIVES: We present new nitrogen isotopic discrimination factor between diets and scalp hairs (Δ(15) NHair-Diet : δ(15) NHair - δ(15) NDiet ) for indigenous residents in three communities in the Papua New Guinea Highlands who consumed various amounts and qualities of protein. The Δ(15) N is important for precise evaluation of the dietary habits of human populations; in both contemporary and traditional lifestyles. Several hypotheses have been proposed regarding factors that affect Δ(15) N values, based largely on observations from animal feeding experiments. However, variations and factors controlling Δ(15) N in humans are not well understood, mainly due to the difficulty of controlling the diets of participants. MATERIALS AND METHODS: These residents were studied because they have maintained relatively traditional dietary habits, which allow quantitative recording of diets. Δ(15) N was estimated by comparing hair δ(15) N values to mean dietary δ(15) N values calculated from the recorded intake of each food item and their δ(15) N values. RESULTS: The results showed that: i) there was a significant difference in Δ(15) N among study locations (3.9 ± 0.9‰ for most urbanized, 5.2 ± 1.0‰ for medium and 5.0 ± 0.9‰ for least urbanized communities; range = 1.2-7.3‰ for all participants); and ii) estimated Δ(15) N values were negatively correlated with several indicators of animal protein intake (% nitrogen in diet: range = 0.9-7.6%). DISCUSSION: We hypothesize that a combination of several factors, which presumably included urea recycling and amino acid and protein recycling and/or de novo synthesis during metabolic processes, altered the Δ(15) N values of the participants.

Development, validation, and use of a semi-quantitative food frequency questionnaire for assessing protein intake in Papua New Guinean Highlanders.

OBJECTIVES: The aim of this article was to develop a semi-quantitative food frequency questionnaire (FFQ) and evaluate its validity to estimate habitual protein intake, and investigate current dietary protein intakes of Papua New Guinea (PNG) Highlanders. METHODS: A 32-item FFQ was developed and tested among 135 healthy male and female volunteers. The FFQ-estimated daily total and animal protein intakes were compared with biomarkers and 3-day Weighed Food Records (WFR) by correlation analyses, Bland-Altman plot analyses and joint classification analyses. RESULTS: The FFQ-estimated total protein intake significantly correlated with urinary nitrogen in the first morning void after adjusting urinary creatinine concentration (r = 0.28, P < 0.01) and the FFQ-estimated animal protein intake significantly correlated with the hair δ(15) N (Spearman's r = 0.34, P < 0.001). The limits of agreement were ±2.39 Z-score residuals for total protein intake and ±2.19 Z-score for animal protein intake, and intra-individual differences increased as protein intake increased. The classification into the same and adjacent quartiles was 66.0% for total protein intake and 73.6% for animal protein intake. Median daily total and animal protein intake estimates from the FFQ and the 3-day WFR showed a good agreement with differences of 0.2 and 4.9 g, respectively. None of the studied communities in the PNG Highlands met the biologically required protein intake; although the community closer to an urban center showed higher protein intake than the more remote communities. CONCLUSIONS: The newly developed 32-item FFQ for PNG Highlanders is applicable for evaluation of protein intake at the individual level. Am. J. Hum. Biol. 27:349-357, 2015. © 2014 Wiley Periodicals, Inc.

Preparedness for threat of chikungunya in the pacific.

Chikungunya virus (CHIKV) caused significant outbreaks of illness during 2005-2007 in the Indian Ocean region. Chikungunya outbreaks have also occurred in the Pacific region, including in Papua New Guinea in 2012; New Caledonia in April 2013; and Yap State, Federated States of Micronesia, in August 2013. CHIKV is a threat in the Pacific, and the risk for further spread is high, given several similarities between the Pacific and Indian Ocean chikungunya outbreaks. Island health care systems have difficulties coping with high caseloads, which highlights the need for early multidisciplinary preparedness. The Pacific Public Health Surveillance Network has developed several strategies focusing on surveillance, case management, vector control, laboratory confirmation, and communication. The management of this CHIKV threat will likely have broad implications for global public health.

Viruses associated with influenza-like-illnesses in Papua New Guinea, 2010.

Influenza-like-illness can be caused by a wide range of respiratory viruses. The etiology of influenza-like-illness in developing countries such as Papua New Guinea is poorly understood. The etiological agents associated with influenza-like-illness were investigated retrospectively for 300 nasopharyngeal swabs received by the Papua New Guinea National Influenza Centre in 2010. Real-time PCR/RT-PCR methods were used for the detection of 13 respiratory viruses. Patients with influenza-like-illness were identified according to the World Health Organization case definition: sudden onset of fever (>38°C), with cough and/or sore throat, in the absence of other diagnoses. At least one viral respiratory pathogen was detected in 66.3% of the samples tested. Rhinoviruses (17.0%), influenza A (16.7%), and influenza B (12.7%) were the pathogens detected most frequently. Children <5 years of age presented with a significantly higher rate of at least one viral pathogen and a significantly higher rate of co-infections with multiple viruses, when compared to all other patients >5 years of age. Influenza B, adenovirus, and respiratory syncytial virus were all detected at significantly higher rates in children <5 years of age. This study confirmed that multiple respiratory viruses are circulating and contributing to the presentation of influenza-like-illness in Papua New Guinea.

Spatio-temporal epidemiology of the cholera outbreak in Papua New Guinea, 2009-2011.

BACKGROUND: Cholera continues to be a devastating disease in many developing countries where inadequate safe water supply and poor sanitation facilitate spread. From July 2009 until late 2011 Papua New Guinea experienced the first outbreak of cholera recorded in the country, resulting in >15,500 cases and >500 deaths. METHODS: Using the national cholera database, we analysed the spatio-temporal distribution and clustering of the Papua New Guinea cholera outbreak. The Kulldorff space-time permutation scan statistic, contained in the software package SatScan v9.2 was used to describe the first 8 weeks of the outbreak in Morobe Province before cholera cases spread throughout other regions of the country. Data were aggregated at the provincial level to describe the spread of the disease to other affected provinces. RESULTS: Spatio-temporal and cluster analyses revealed that the outbreak was characterized by three distinct phases punctuated by explosive propagation of cases when the outbreak spread to a new region. The lack of road networks across most of Papua New Guinea is likely to have had a major influence on the slow spread of the disease during this outbreak. CONCLUSIONS: Identification of high risk areas and the likely mode of spread can guide government health authorities to formulate public health strategies to mitigate the spread of the disease through education campaigns, vaccination, increased surveillance in targeted areas and interventions to improve water, sanitation and hygiene.

An investigation into febrile illnesses of unknown aetiology in Wipim, Papua New Guinea.

In Papua New Guinea the aetiology of febrile illnesses remains poorly characterized, mostly due to poor diagnostic facilities and the inaccessibility of much of the rural areas of the country. We investigated the aetiological agents of febrile illnesses for 136 people presenting to Wipim Health Centre in Western Province, Papua New Guinea. Arboviral and rickettsial real-time polymerase chain reaction (PCR) assays, malaria blood smears and a malaria PCR test were used to identify pathogens associated with a history of fever. In 13% (n = 18) of cases an aetiological agent was identified. Dengue virus type 1 was detected in 11% (n = 15) of the samples tested and malaria in 2% (n = 3). None of the other arboviral or rickettsial pathogens tested for were detected in any of the samples. Although dengue viruses have been identified in Papua New Guinea using serological methods, this study represents the first direct detection of dengue in the country. The detection of malaria, on the other hand, was surprisingly low considering the previous notion that this was a hyperendemic region of Papua New Guinea.

Prediction of viral spillover risk based on the mass action principle.

Infectious zoonotic disease emergence, through spillover events, is of global concern and has the potential to cause significant harm to society, as recently demonstrated by COVID-19. More than 70% of the 400 infectious diseases that emerged in the past five decades have a zoonotic origin, including all recent pandemics. There have been several approaches used to predict the risk of spillover through some of the known or suspected infectious disease emergence drivers, largely using correlative approaches. Here, we predict the spatial distribution of spillover risk by approximating general transmission through animal and human interactions. These mass action interactions are approximated through the multiplication of the spatial distribution of zoonotic virus diversity and human population density. Although our results indicate higher risk in regions along the equator and in Southeast Asia where both virus diversity and human population density are high, it should be noted that this is primarily a conceptual exercise. We compared our spillover risk map to key factors, including the model inputs of zoonotic virus diversity estimate map, human population density map, and the spatial distribution of species richness. Despite the limitations of this approach, this viral spillover map is a step towards developing a more comprehensive spillover risk prediction system to inform global monitoring.