Model analysis and data validation of structured prevention and control interruptions of emerging infectious diseases.

The design of optimized non-pharmaceutical interventions (NPIs) is critical to the effective control of emergent outbreaks of infectious diseases such as SARS, A/H1N1 and COVID-19 and to ensure that numbers of hospitalized cases do not exceed the carrying capacity of medical resources. To address this issue, we formulated a classic SIR model to include a close contact tracing strategy and structured prevention and control interruptions (SPCIs). The impact of the timing of SPCIs on the maximum number of non-isolated infected individuals and on the duration of an infectious disease outside quarantined areas (i.e. implementing a dynamic zero-case policy) were analyzed numerically and theoretically. These analyses revealed that to minimize the maximum number of non-isolated infected individuals, the optimal time to initiate SPCIs is when they can control the peak value of a second rebound of the epidemic to be equal to the first peak value. More individuals may be infected at the peak of the second wave with a stronger intervention during SPCIs. The longer the duration of the intervention and the stronger the contact tracing intensity during SPCIs, the more effective they are in shortening the duration of an infectious disease outside quarantined areas. The dynamic evolution of the number of isolated and non-isolated individuals, including two peaks and long tail patterns, have been confirmed by various real data sets of multiple-wave COVID-19 epidemics in China. Our results provide important theoretical support for the adjustment of NPI strategies in relation to a given carrying capacity of medical resources.

The global patent landscape of emerging infectious disease monkeypox.

BACKGROUND: Monkeypox is an emerging infectious disease with confirmed cases and deaths in several parts of the world. In light of this crisis, this study aims to analyze the global knowledge pattern of monkeypox-related patents and explore current trends and future technical directions in the medical development of monkeypox to inform research and policy. METHODS: A comprehensive study of 1,791 monkeypox-related patents worldwide was conducted using the Derwent patent database by descriptive statistics, social network method and linear regression analysis. RESULTS: Since the 21st century, the number of monkeypox-related patents has increased rapidly, accompanied by increases in collaboration between commercial and academic patentees. Enterprises contributed the most in patent quantity, whereas the initial milestone patent was filed by academia. The core developments of technology related to the monkeypox include biological and chemical medicine. The innovations of vaccines and virus testing lack sufficient patent support in portfolios. CONCLUSIONS: Monkeypox-related therapeutic innovation is geographically limited with strong international intellectual property right barriers though it has increased rapidly in recent years. The transparent licensing of patent knowledge is driven by the merger and acquisition model, and the venture capital, intellectual property and contract research organization model. Currently, the patent thicket phenomenon in the monkeypox field may slow the progress of efforts to combat monkeypox. Enterprises should pay more attention to the sharing of technical knowledge, make full use of drug repurposing strategies, and promote innovation of monkeypox-related technology in hotspots of antivirals (such as tecovirimat, cidofovir, brincidofovir), vaccines (JYNNEOS, ACAM2000), herbal medicine and gene therapy.

Vaccination against emerging and reemerging infectious diseases in places of detention: a global multistage scoping review.

Background: Despite the elevated risks of infection transmission, people in prisons frequently encounter significant barriers in accessing essential healthcare services in many countries. The present scoping review aimed to evaluate the state of availability and model of delivery of vaccination services within correctional facilities across the globe. Methods: Following the methodological framework for scoping reviews and adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for scoping reviews criteria, we conducted a systematic search across four peer-reviewed literature databases (Medline via PubMed, Web of Science, the Cochrane Library, Science Direct, and EBSCO), as well as 14 sources of grey literature. Two researchers meticulously examined the identified papers independently to extract pertinent data published between 2012 and 2022. The quality of the selected publications was assessed using established quality assessment tools. Results: Of the 11,281 identified papers 52 met the inclusion criteria. With the exception of one, all the included publications presented data from high-income countries, predominantly originating from the United States. Across the world, the most prevalent vaccines available in prison settings were COVID-19 and HBV vaccines, typically distributed in response to health crises such as pandemics, epidemics, and local outbreaks. Vaccine coverage and uptake rates within correctional facilities displayed noteworthy disparities among various countries and regions. Besides, individual and organizational barriers and facilitating factors of vaccination in prison settings emerged and discussed in the text. Discussion: The lack of vaccination services combined with low rates of vaccination coverage and uptake among people living and working in correctional facilities represents a cause for concern. Prisons are not isolated from the broader community, therefore, efforts to increase vaccine uptake among people who live and work in prisons will yield broader public health benefits.

Six dilemmas for stakeholders inherently affecting data sharing during a zoonotic (re-)emerging infectious disease outbreak response.

BACKGROUND: Timely access to outbreak related data, particularly in the early events of a spillover, is important to support evidence based control measures in response to outbreaks of zoonotic Emerging Infectious Diseases (EID). Yet, this is impeded by several barriers that need to be understood to promote timely sharing of data. Using the MERS epidemic as a model for a zoonotic EID outbreak, this study sought to provide an in-depth understanding of data sharing practices. METHODS: Semi-structured interviews with 25 experts were conducted, along with Focus Group Discussions with 15 additional experts. A root-cause analysis was performed to examine the causal relationships between barriers. Enablers were mapped to the root-cause analysis to understand their influence on the barriers. Finally, root causes were placed in context of core dilemmas identified from the qualitative analysis. FINDINGS: Eight barriers to data sharing were identified, related to collaboration, technical preparedness, regulations, and (conflict of) interests, and placed in the context of six dilemmas inherent to the multi-stakeholder collaboration required for a zoonotic outbreak response. Fourteen identified enablers showed the willingness of stakeholders to overcome or circumvent these barriers, but also indicated the inherent trial and error nature of implementing such enablers. INTERPRETATION: Addressing the barriers requires solutions that must consider the complexity and interconnectedness of the root causes underlying them, and should consider the distinct scopes and interests of the different stakeholders. Insights provided by this study can be used to encourage data sharing practices for future outbreaks FUNDING: Wellcome Trust and UK Aid; EU-H2020 Societal Challenges (grant agreement no. 643476), Nederlandse Organisatie voor Wetenschappelijk Onderzoek (VI.Veni.201S.044).

Investigating the impact of vaccine hesitancy on an emerging infectious disease: a mathematical and numerical analysis.

Throughout the last two centuries, vaccines have been helpful in mitigating numerous epidemic diseases. However, vaccine hesitancy has been identified as a substantial obstacle in healthcare management. We examined the epidemiological dynamics of an emerging infection under vaccination using an SVEIR model with differential morbidity. We mathematically analyzed the model, derived R0, and provided a complete analysis of the bifurcation at R0=1. Sensitivity analysis and numerical simulations were used to quantify the tradeoffs between vaccine efficacy and vaccine hesitancy on reducing the disease burden. Our results indicated that if the percentage of the population hesitant about taking the vaccine is 10%, then a vaccine with 94% efficacy is required to reduce the peak of infections by 40%. If 60% of the population is reluctant about being vaccinated, then even a perfect vaccine will not be able to reduce the peak of infections by 40%.

Emerging zoonotic diseases in Southeast Asia in the period 2011-2022: a systematic literature review.

As COVID-19 has shown, pandemics and outbreaks of emerging infections such as Zika, Nipah, monkeypox and antimicrobial-resistant pathogens, especially emerging zoonotic diseases, continue to occur and may even be increasing in Southeast Asia. In addition, these infections often result from environmental changes and human behaviour. Overall, public health surveillance to identify gaps in the literature and early warning signs are essential in this region. A systematic review investigated the prevalence of emerging zoonotic diseases over 11 years from 2011 to 2022 in Southeast Asia to understand the status of emerging zoonotic diseases, as well as to provide necessary actions for disease control and prevention in the region. During the 2011-2022 period, studies on pigs, poultry, ruminants, companion animals and wildlife in Southeast Asia were reviewed thoroughly to assess the quality of reporting items for inclusion in the systematic review. The review was performed on 26 studies of pigs, 6 studies of poultry, 21 studies of ruminants, 28 studies of companion animals and 25 studies of wildlife in Southeast Asia, which provide a snapshot of the prevalence of the emerging zoonotic disease across the country. The findings from the review showed that emerging zoonotic diseases were prevalent across the region and identified a few zoonotic diseases associated with poultry, mainly stemming from Cambodia and Vietnam, as high priority in Southeast Asia.Clinical relevance: Appropriate prevention and control measures should be taken to mitigate the emerging zoonotic diseases in Southeast Asia.

Daily Hospital Emerging Infectious Disease(EID) Workflow & Data Processing Automation.

Following the onset of the covid pandemic two years ago, the Ministry of Health(MOH)'s required all health care cluster groups to provide daily reporting of the emergency department as well as the inpatient situation in the respective healthcare institutions for oversight of the covid situation. In view of the improvements in the data availability and relief of the tedious manual collation, DAO was entrusted with the task to help enable and setup the standardized report and generation process moving forward.

"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.

Ineffective responses to unlikely outbreaks: Hypothesis building in newly-emerging infectious disease outbreaks.

Over the last 30 years, there has been significant investment in research and infrastructure aimed at mitigating the threat of newly emerging infectious diseases (NEID). Core epidemiological processes, such as outbreak investigations, however, have received little attention and have proceeded largely unchecked and unimproved. Using ethnographic material from an investigation into a cryptic encephalitis outbreak in the Brong-Ahafo Region of Ghana in 2010-2013, in this paper we trace processes of hypothesis building and their relationship to the organizational structures of the response. We demonstrate how commonly recurring features of NEID investigations produce selective pressures in hypothesis building that favor iterations of pre-existing "exciting" hypotheses and inhibit the pursuit of alternative hypotheses, regardless of relative likelihood. These findings contribute to the growing anthropological and science and technology studies (STS) literature on the epistemic communities that coalesce around suspected NEID outbreaks and highlight an urgent need for greater scrutiny of core epidemiological processes.

Population age and household structures shape transmission dynamics of emerging infectious diseases: a longitudinal microsimulation approach.

Host population demographics and patterns of host-to-host interactions are important drivers of heterogeneity in infectious disease transmission. To improve our understanding of how population structures and changes therein influence disease transmission dynamics at the individual and population level, we model a dynamic age- and household-structured population using longitudinal microdata drawn from Belgian census and population registers. At different points in time, we simulate the spread of a close-contact infectious disease and vary the age profiles of infectiousness and susceptibility to reflect specific infections (e.g. influenza and SARS-CoV-2) using a two-level mixing model, which distinguishes between exposure to infection in the household and exposure in the community. We find that the strong relationship between age and household structures, in combination with social mixing patterns and epidemiological parameters, shape the spread of an emerging infection. Disease transmission in the adult population in particular is to a large degree explained by differential household compositions and not just household size. Moreover, we highlight how demographic processes alter population structures in an ageing population and how these in turn affect disease transmission dynamics across population groups.

Financial influence on global risks of zoonotic emerging and re-emerging diseases: an integrative analysis.

BACKGROUND: Emerging and re-emerging infectious diseases (EIDs), such as Ebola virus disease and highly pathogenic influenza, are serious threats to human health and wellbeing worldwide. The financial sector has an important, yet often ignored, influence as owners and investors in industries that are associated with anthropogenic land-use changes in ecosystems linked to increased EIDs risks. We aimed to analyse financial influence associated with EIDs risks that are affected by anthropogenic land-use changes. We also aimed to provide empirical assessments of such influence to help guide engagements by governments, private organisations, and non-governmental organisations with the financial sector to advance a planetary health agenda. METHODS: For this integrative analysis, we identified regions in the world where there was evidence of a connection between EIDs and anthropogenic land-use changes between Nov 9, 1999, and Oct 25, 2021, through a targeted literature review of academic literature and grey literature to identify evidence of drivers of anthropogenic land-use change and their association with commodity production in these regions. We only included publications in English that showed a connection between deforestation and the production of one or more commodities. Publications merely describing spatial or temporal land-use change dynamics (eg, a reduction of forest or an increase of palm-oil plantations) were excluded. As we were assessing financial influence on corporate activities through ownership specifically, we focused our analysis on publicly listed companies. Equity data and data about ownership structure were extracted from Orbis, a company information database. We assessed financial influence by identifying financial entities with the largest equity ownership, descriptively mapping transboundary connections between investors and publicly listed companies. FINDINGS: 227 public and private companies operating in five economic sectors (ie, production of palm oil, pulp and wood products, cocoa, soybeans, and beef) between Dec 15, 2020, and March 8, 2021, were identified. Of these 227, 99 (44%) were publicly listed companies, with 2310 unique shareholders. These publicly listed companies operated in six geographical regions, resulting in nine case-study regions. 54 (55%) companies with complete geographical information were included in the countries network. Four financial entities (ie, Dimensional, Vanguard, BlackRock, and Norway's sovereign wealth fund) each had ownership in 39 companies or more in three of the case-study regions (ie, north America, east Asia, and Europe). Four large US-based asset managers (ie, Vanguard, BlackRock, T Rowe Price, and State Street) were the largest owners of publicly listed companies in terms of total equity size, with ownership amounts for these four entities ranging from US$8 billion to $21 billion. The specific patterns of cross-national ownership depended on the region of interest; for example, financial influence on EIDs risks that was associated with commodity production in southeast and east Asia came from not only global asset managers but also Malaysian, Chinese, Japanese, and Korean financial entities. India, Brazil, the USA, Mexico, and Argentina were the countries towards which investments were most directed. INTERPRETATION: Although commodity supply chains and financial markets are highly globalised, a small number of investors and countries could be viewed as disproportionally influential in sectors that increase EIDs risks. Such financial influence could be used to develop and implement effective policies to reduce ecological degradation and mitigate EIDs risks and their effects on population health. FUNDING: Formas and Networks of Financial Rupture-how cascading changes in the climate and ecosystems could impact on the financial sector.

Role of Laboratory in Emerging Infectious Disease Control in Iran, Pasteur Institute of Iran, and national laboratory network.

Strengthening surveillance systems is a key aspect of outbreak response and was particularly important during the COVID-19 pandemic. Respiratory pathogens spread rapidly, and laboratory capacity is key to monitoring the spread. Prior to the pandemic, Iran had established a rapid response team and laboratory network to provide identification, monitoring, and detection of emerging infectious diseases, but did not have the laboratory capacity to respond to COVID-19. Following the announcement of the COVID-19 pandemic, the rapid response team diverted all attention to supporting COVID-19 surveillance. Iran built on the existing national laboratory infrastructure to incorporate SARS-CoV-2 surveillance into the response network. Based on existing international protocols, in-house molecular diagnosis capacity was operationalized, and commercial controls and assays were acquired and validated to national standards. The first COVID-19 laboratory was operational by January 25, less than 4 weeks before the initial detection of SARS-CoV-2 was announced. Assays and support were expanded and rolled out to form the COVID-19 National Laboratory Network, which consists of 560 multi-sectoral laboratories covering all provinces of Iran. The national laboratory network supports a wide range of operational capacities, including assay validation and protocol development, quality assurance, respiratory pathogen diagnosis and surveillance, and variant identification and assessment using multiple sequencing platforms. This network has supported the testing of over 55 million samples over the past 36 months using RT-qPCR and has sequenced approximately 2200 samples across the country, contributing the data to international databases, including GISAID.

Optimal vaccination ages for emerging infectious diseases under limited vaccine supply.

Rational allocation of limited vaccine resources is one of the key issues in the prevention and control of emerging infectious diseases. An age-structured infectious disease model with limited vaccine resources is proposed to explore the optimal vaccination ages. The effective reproduction number [Formula: see text] of the epidemic disease is computed. It is shown that the reproduction number is the threshold value for eradicating disease in the sense that the disease-free steady state is globally stable if [Formula: see text] and there exists a unique endemic equilibrium if [Formula: see text]. The effective reproduction number is used as an objective to minimize the disease spread risk. Using the epidemic data from the early spread of Wuhan, China and demographic data of Wuhan, we figure out the strategies to distribute the vaccine to the age groups to achieve the optimal vaccination effects. These analyses are helpful to the design of vaccination schedules for emerging infectious diseases.

Implementation and expansion of laboratory capacity for molecular diagnostics in response to COVID-19 and preparedness for other emerging infectious diseases in the Islamic Emirate of Afghanistan.

Background: Afghanistan experienced various outbreaks before and during the Covid-19 pandemic, including dengue, Crimean Congo hemorrhagic fever (CCHF), measles, and acute watery diarrhea (AWD). Diagnostic and surveillance support was limited, with only the Central Public Health Laboratory equipped to handle outbreak responses. This article highlights initiatives taken to improve diagnostic capabilities for COVID-19 and other outbreaks of public health concern encountered during the pandemic. Background: The World Health Organization (WHO) Afghanistan Country Office collaborated with the WHO Eastern Mediterranean Regional Office (EMRO), Central Public Health Laboratory (CPHL), and National Influenza Center (NIC) to enhance COVID-19 diagnostic capacity at national and subnational facilities. To alleviate pressure on CPHL, a state-of-the-art laboratory was established at the National Infectious Disease Hospital (NIDH) in Kabul in 2021-2022, while WHO EMRO facilitated the regionalization of testing to subnational facilities for dengue, CCHF, and AWD in 2022-2023. Results: COVID-19 testing capacity expanded nationwide to 34 Biosafety Level II labs, improving diagnosis time. Daily testing rose from 1000 in 2020 to 9200 in 2023, with 848,799 cumulative tests. NIDH identified 229 CCHF cases and 45 cases nationally. Dengue and CCHF testing, decentralized to Nangarhar and Kandahar labs, identified 338 dengue and 18 CCHF cases. AWD testing shifted to NIDH and five subnational facilities (Kandahar, Paktia, Balkh, Herat, and Nangarhar labs), while measles testing also decentralized to nine subnational facilities. Conclusion: Afghanistan implemented a remarkable, multisectoral response to priority pathogens. The nation now possesses diagnostic expertise at national and subnational levels, supported by genomic surveillance. Future efforts should concentrate on expanding and sustaining this capacity to enhance public health responses.

Leveraging Donor Populations to Study the Epidemiology and Pathogenesis of Transfusion-Transmitted and Emerging Infectious Diseases.

The tragedy of transfusion-associated hepatitis and HIV spurred a decades-long overhaul of the regulatory oversight and practice of blood transfusion. Consequent to improved donor selection, testing, process control, clinical transfusion practice and post-transfusion surveillance, transfusion in the United States and other high-income countries is now a very safe medical procedure. Nonetheless, pathogens continue to emerge and threaten the blood supply, highlighting the need for a proactive approach to blood transfusion safety. Blood donor populations and the global transfusion infrastructure are under-utilized resources for the study of infectious diseases. Blood donors are large, demographically diverse subsets of general populations for whom cross-sectional and longitudinal samples are readily accessible for serological and molecular testing. Blood donor collection networks span diverse geographies, including in low- and middle-income countries, where agents, especially zoonotic pathogens, are able to emerge and spread, given limited tools for recognition, surveillance and control. Routine laboratory storage and transportation, coupled with data capture, afford access to rich epidemiological data to assess the epidemiology and pathogenesis of established and emerging infections. Subsequent to the State of the Science in Transfusion Medicine symposium in 2022, our working group (WG), "Emerging Infections: Impact on Blood Science, the Blood Supply, Blood Safety, and Public Health" elected to focus on "leveraging donor populations to study the epidemiology and pathogenesis of transfusion-transmitted and emerging infectious diseases." The 5 landmark studies span (1) the implication of hepatitis C virus in post-transfusion hepatitis, (2) longitudinal evaluation of plasma donors with incident infections, thus informing the development of a widely used staging system for acute HIV infection, (3) explication of the dynamics of early West Nile Virus infection, (4) the deployment of combined molecular and serological donor screening for Babesia microti, to characterize its epidemiology and infectivity and facilitate routine donor screening, and (5) national serosurveillance for SARS-CoV-2 during the COVID-19 pandemic. The studies highlight the interplay between infectious diseases and transfusion medicine, including the imperative to ensure blood transfusion safety and the broader application of blood donor populations to the study of infectious diseases.

Emerging infectious disease surveillance using a hierarchical diagnosis model and the Knox algorithm.

Emerging infectious diseases are a critical public health challenge in the twenty-first century. The recent proliferation of such diseases has raised major social and economic concerns. Therefore, early detection of emerging infectious diseases is essential. Subjects from five medical institutions in Beijing, China, which met the spatial-specific requirements, were analyzed. A quality control process was used to select 37,422 medical records of infectious diseases and 56,133 cases of non-infectious diseases. An emerging infectious disease detection model (EIDDM), a two-layer model that divides the problem into two sub-problems, i.e., whether a case is an infectious disease, and if so, whether it is a known infectious disease, was proposed. The first layer model adopts the binary classification model TextCNN-Attention. The second layer is a multi-classification model of LightGBM based on the one-vs-rest strategy. Based on the experimental results, a threshold of 0.5 is selected. The model results were compared with those of other models such as XGBoost and Random Forest using the following evaluation indicators: accuracy, sensitivity, specificity, positive predictive value, and negative predictive value. The prediction performance of the first-layer TextCNN is better than that of other comparison models. Its average specificity for non-infectious diseases is 97.57%, with an average negative predictive value of 82.63%, indicating a low risk of misdiagnosing non-infectious diseases as infectious (i.e., a low false positive rate). Its average positive predictive value for eight selected infectious diseases is 95.07%, demonstrating the model's ability to avoid misdiagnoses. The overall average accuracy of the model is 86.11%. The average prediction accuracy of the second-layer LightGBM model for emerging infectious diseases reaches 90.44%. Furthermore, the response time of a single online reasoning using the LightGBM model is approximately 27 ms, which makes it suitable for analyzing clinical records in real time. Using the Knox method, we found that all the infectious diseases were within 2000 m in our case, and a clustering feature of spatiotemporal interactions (P < 0.05) was observed as well. Performance testing and model comparison results indicated that the EIDDM is fast and accurate and can be used to monitor the onset/outbreak of emerging infectious diseases in real-world hospitals.

A global examination of ecological niche modeling to predict emerging infectious diseases: a systematic review.

Introduction: As emerging infectious diseases (EIDs) increase, examining the underlying social and environmental conditions that drive EIDs is urgently needed. Ecological niche modeling (ENM) is increasingly employed to predict disease emergence based on the spatial distribution of biotic conditions and interactions, abiotic conditions, and the mobility or dispersal of vector-host species, as well as social factors that modify the host species' spatial distribution. Still, ENM applied to EIDs is relatively new with varying algorithms and data types. We conducted a systematic review (PROSPERO: CRD42021251968) with the research question: What is the state of the science and practice of estimating ecological niches via ENM to predict the emergence and spread of vector-borne and/or zoonotic diseases? Methods: We searched five research databases and eight widely recognized One Health journals between 1995 and 2020. We screened 383 articles at the abstract level (included if study involved vector-borne or zoonotic disease and applied ENM) and 237 articles at the full-text level (included if study described ENM features and modeling processes). Our objectives were to: (1) describe the growth and distribution of studies across the types of infectious diseases, scientific fields, and geographic regions; (2) evaluate the likely effectiveness of the studies to represent ecological niches based on the biotic, abiotic, and mobility framework; (3) explain some potential pitfalls of ENM algorithms and techniques; and (4) provide specific recommendation for future studies on the analysis of ecological niches to predict EIDs. Results: We show that 99% of studies included mobility factors, 90% modeled abiotic factors with more than half in tropical climate zones, 54% modeled biotic conditions and interactions. Of the 121 studies, 7% include only biotic and mobility factors, 45% include only abiotic and mobility factors, and 45% fully integrated the biotic, abiotic, and mobility data. Only 13% of studies included modifying social factors such as land use. A majority of studies (77%) used well-recognized ENM algorithms (MaxEnt and GARP) and model selection procedures. Most studies (90%) reported model validation procedures, but only 7% reported uncertainty analysis. Discussion: Our findings bolster ENM to predict EIDs that can help inform the prevention of outbreaks and future epidemics. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier (CRD42021251968).

Emerging infectious diseases, focus on infection prevention, environmental survival and germicide susceptibility: SARS-CoV-2, Mpox, and Candida auris.

BACKGROUND: New and emerging infectious diseases continue to represent a public health threat. Emerging infectious disease threats include pathogens increasing in range (eg, Mpox), zoonotic microbes jumping species lines to cause sustained infections in humans via person-to-person transmission (SARS-CoV-2) and multidrug-resistant pathogens (eg, Candida auris). MATERIALS AND METHODS: We searched the published English literature and reviewed the selected articles on SARS-CoV-2, Mpox, and Candida auris with a focus on environmental survival, contamination of the patient's hospital environment, susceptibility of the pathogen to antiseptics and disinfectants and infection prevention recommendations. RESULTS: All three pathogens (ie, SARS-CoV-2, Mpox, and Candida auris) can survive on surfaces for minutes to hours and for Mpox and C auris for days. Currently available antiseptics (eg, 70%-90% alcohol hand hygiene products) are active against SARS-CoV-2, Mpox and C auris. The U.S Environmental Protection Agency provides separate lists of surface disinfectants active against SARS-CoV-2, Mpox, and C auris. DISCUSSION: The risk of environment-to-patient transmission of SARS-CoV-2, Mpox and Candida auris, is very low, low-moderate and high, respectively. In the absence of appropriate patient isolation and use of personal protection equipment, the risk of patient-to-health care provider transmission of SARS-CoV-2, Mpox, and C auris is high, moderate and low, respectively. CONCLUSIONS: Appropriate patient isolation, use of personal protective equipment by health care personnel, hand hygiene, and surface disinfection can protect patients and health care personnel from acquiring SARS-CoV-2, Mpox, and C auris from infected patients.