Evaluating infection risks in buses based on passengers' dynamic temporal and typical spatial scenarios: A case study of COVID-19

Conventional buses, as an indispensable part of the urban public transport system, impose cross-infection risks on passengers. To assess differential risks due to dynamic staying durations and locations, this study considered four spatial distributions (i = 1-4) and six temporal scenarios (j = 1-6) of buses. Based on field measurements and a risk assessment approach combining both short-range and room-scale effects, risks are evaluated properly. The results showed that temporal asynchrony between infected and susceptible individuals significantly affects disease transmission rates. The Control Case assumes that infected and susceptible individuals enter and leave synchronously. However, ignoring temporal asynchrony scenarios, i.e., the Control Case, resulted in overestimation (+30.7 % to +99.6 %) or underestimation (-15.2 % to -69.9 %) of the actual risk. Moreover, the relative difference ratios of room-scale risks between the Control Case and five temporal scenarios are impacted by ventilation. Short-range risk exists only if infected and susceptible individuals have temporal overlap on the bus. Considering temporal and spatial asynchrony, a more realistic total reproduction number (R) can be obtained. Subsequently, the total R was assessed under five temporal scenarios. On average, for the Control Case, the total R was estimated to be +27.3 % higher than j = 1, -9.3 % lower than j = 2, +12.8 % higher than j = 3, +33.0 % lower than j = 4, and + 77.6 % higher than j = 5. This implies the need for a combination of active prevention and real-time risk monitoring to enable rigid travel demand and control the spread of the epidemic.

Mathematical modeling and stability analysis of the novel fractional model in the Caputo derivative operator: A case study

The fundamental goal of this research is to suggest a novel mathematical operator for modeling visceral leishmaniasis, specifically the Caputo fractional-order derivative. By utilizing the Fractional Euler Method, we were able to simulate the dynamics of the fractional visceral leishmaniasis model, evaluate the stability of the equilibrium point, and devise a treatment strategy for the disease. The endemic and disease-free equilibrium points are studied as symmetrical components of the proposed dynamical model, together with their stabilities. It was shown that the fractional calculus model was more accurate in representing the situation under investigation than the classical framework at α = 0.99 and α = 0.98. We provide justification for the usage of fractional models in mathematical modeling by comparing results to real-world data and finding that the new fractional formalism more accurately mimics reality than did the classical framework. Additional research in the future into the fractional model and the impact of vaccinations and medications is necessary to discover the most effective methods of disease control.

Ecological and social factors influence interspecific pathogens occurrence among bees

The interspecific transmission of pathogens can occur frequently in the environment. Among wild bees, the main spillover cases are caused by pathogens associated with Apis mellifera, whose colonies can act as reservoirs. Due to the limited availability of data in Italy, it is challenging to accurately assess the impact and implications of this phenomenon on the wild bee populations. In this study, a total of 3372 bees were sampled from 11 Italian regions within the BeeNet project, evaluating the prevalence and the abundance of the major honey bee pathogens (DWV, BQCV, ABPV, CBPV, KBV, Nosema ceranae, Ascosphaera apis, Crithidia mellificae, Lotmaria passim, Crithidia bombi). The 68.4% of samples were positive for at least one pathogen. DWV, BQCV, N. ceranae and CBPV showed the highest prevalence and abundance values, confirming them as the most prevalent pathogens spread in the environment. For these pathogens, Andrena, Bombus, Eucera and Seladonia showed the highest mean prevalence and abundance values. Generally, time trends showed a prevalence and abundance decrease from April to July. In order to predict the risk of infection among wild bees, statistical models were developed. A low influence of apiary density on pathogen occurrence was observed, while meteorological conditions and agricultural management showed a greater impact on pathogen persistence in the environment. Social and biological traits of wild bees also contributed to defining a higher risk of infection for bivoltine, communal, mining and oligolectic bees. Out of all the samples tested, 40.5% were co-infected with two or more pathogens. In some cases, individuals were simultaneously infected with up to five different pathogens. It is essential to increase knowledge about the transmission of pathogens among wild bees to understand dynamics, impact and effects on pollinator populations. Implementing concrete plans for the conservation of wild bee species is important to ensure the health of wild and human-managed bees within a One-Health perspective.

Beyond duodenoscope-transmitted infections: Analysis of surface bioburden and UV-C mitigation within a tertiary care endoscopy unit

BACKGROUND

An inpatient endoscopy unit is a care hub for patients from throughout the hospital and can be the site of health care-associated infections (HAIs). Shared surfaces and other nonmedical devices (keyboards) have been increasingly recognized as sites of pathogen transmission. Beyond standard cleaning of high-touch target areas, we queried whether the addition of automated devices delivering low-intensity doses of ultraviolet (UV)-C radiation could further reduce bioburden in an academic endoscopy unit.

METHODS

Bioburden on previously identified high-touch/communal surfaces was measured before and after the installation of automated, low-intensity UV-light emitting devices (UV Angel) that passively monitor and disinfect targeted surfaces with Ultraviolet-C light (UV-C) light.

RESULTS

High-touch sites (keyboards) had a baseline bacterial contamination of >80%, whereas individual procedure rooms and common areas had a >57% contamination rate. Following the implementation of automated UV-C light decontamination, bioburden was reduced on average by >91% at high-touch surfaces and within procedure rooms.

DISCUSSION/CONCLUSIONS

Nonsterile hubs of patient care could serve as sites of "silent" HAI transmission. We have identified high-touch surfaces within an endoscopy unit that have a high bioburden of bacterial contamination and demonstrated that the installation of passive, automated UV-C light disinfection devices can reduce bioburden significantly, possibly mitigating HAI transmission between patients.

Utility of Mycobacterium tuberculosis genome sequencing snapshots to assess transmission dynamics over time

We explored the utility of brief Mycobacterium tuberculosis whole-genome sequencing (WGS) "snapshots" at a sentinel site within Lima, Peru for evaluating local transmission dynamics over time. Within a 17 km2 area, 15/70 (21%) isolates with WGS collected during 2011-2012 and 22/81 (27%) collected during 2020-2021 were clustered (p = 0.414), and additional isolates clustered with those from outside the area. Isolates from the later period were disproportionately related to large historic clusters in Lima from the earlier period. WGS snapshots at a sentinel site may not be useful for monitoring transmission, but monitoring the persistence of large transmission clusters might be.

The spatial spread of HIV in Malawi: An individual-based mathematical model

Background

The prevalence of HIV varies greatly between and within countries. We aimed to build a comprehensive mathematical modelling tool capable of exploring the reasons of this heterogeneity and test its applicability by simulating the Malawian HIV epidemic.

Methods

We developed a flexible individual-based mathematical model for HIV transmission that comprises a spatial representation and individual-level determinants. We tested this model by calibrating it to the HIV epidemic in Malawi and exploring whether the heterogeneity in HIV prevalence could be reproduced. We ran the model for 1975-2030 with five alternative realizations of the geographical structure and mobility: (I) no geographical structure; 28 administrative districts including (II) only permanent inter-district relocations, (III) inter-district permanent relocations and casual sexual relationships, or (IV) permanent relocations between districts and to/from abroad and inter-district casual sex; and (V) a grid of 10 × 10km2 cells, with permanent relocations and between-cell casual relationships. We assumed HIV was present in 1975 in the districts with >10 % prevalence in 2010. We calibrated the models to national and district-level prevalence estimates.

Results

Reaching the national prevalence required all adults to have at least 22 casual sex acts/year until 1990. Models II, III and V reproduced the geographical heterogeneity in prevalence in 2010 to some extent if between-district relationships were excluded (Model II; 4.9 %-21.1 %). Long-distance casual partnership mixing mitigated the differences in prevalence substantially (range across districts 4.1%-18.9 % in 2010 in Model III; 4.0%-17.6 % in Model V); with international migration the differences disappeared (Model IV; range across districts 6.9%-13.3 % in 2010). National prevalence decreased to 5 % by 2030.

Conclusion

Earlier introduction of HIV into the Southern part of Malawi may cause some level of heterogeneity in HIV prevalence. Other factors such as sociobehavioural characteristics are likely to have a major impact and need investigation.

Learning from the covid-19 outbreaks in long-term care facilities: a systematic review

BACKGROUND

The COVID-19 pandemic has devastatingly affected Long-Term Care Facilities (LTCF), exposing aging people, staff members, and visitors. The world has learned through the pandemic and lessons can be taken to adopt effective measures to deal with COVID-19 outbreaks in LTCF. We aimed to systematically review the available evidence on the effect of measures to minimize the risk of transmission of COVID-19 in LTCs during outbreaks since 2021.

METHODS

The search method was guided by the preferred reporting items for systematic reviews (PRISMA) and the reporting guideline synthesis without meta-analysis (SWiM) in systematic reviews. The search was performed in April 2023. Observational and interventional studies from the databases of PubMed, Web of Science, Scopus, Cochrane Systematic Reviews, CINAHL, and Academic Search were systematically reviewed. We included studies conducted in the LTCF with outbreaks that quantitatively assess the effect of non-pharmacological measures on cases of COVID-19. Two review authors independently reviewed titles for inclusion, extracted data, and undertook the risk of bias according to pre-specified criteria. The quality of studies was analyzed using the Joanna Briggs Institute Critical Appraisal.

RESULTS

Thirteen studies were included, with 8442 LTCF experiencing COVID-19 outbreaks and 598 thousand participants (residents and staff members). Prevention and control of COVID-19 infection interventions were grouped into three themes: strategic, tactical, and operational measures. The strategic measures reveal the importance of COVID-19 prevention and control as LTCF structural characteristics, namely the LTCF size, new admissions, infection control surveillance, and architectural structure. At the tactical level, the lack of personal and long staff shifts is related to COVID-19's spread. Operational measures with a favorable effect on preventing COVID-19 transmission are sufficient. Personal protective equipment stock, correct mask use, signaling, social distancing, and resident cohorting.

CONCLUSIONS

Operational, tactical, and strategic approaches may have a favorable effect on preventing the spread of COVID-19 in LTCFs experiencing outbreaks. Given the heterogeneous nature of the measures, performing a meta-analysis was not possible. Future research should use more robust study designs to explore similar infection control measures in LTCFs during endemic situations with comparable outbreaks.

TRIAL REGISTRATION

The protocol of this systematic review was registered in PROSPERO (CRD42020214566).

Understanding the interface between European wild boar (Sus scrofa) and domestic pigs (Sus scrofa domesticus) in Sweden through a questionnaire study

BACKGROUND

In recent years, the wildlife/livestock interface has attracted increased attention due to disease transmission between wild and domestic animal populations. The ongoing spread of African swine fever (ASF) in European wild boar (Sus scrofa) emphasize the need for further understanding of the wildlife/livestock interface to prevent disease spill-over between the wild and domestic populations. Although wild boar may also act as a potential source for other infectious disease agents, ASF is currently the most severe threat from wild boar to domestic pigs. To gather information on the wild boar situation at commercial pig producing farms in Sweden, a digital questionnaire survey was distributed through the animal health services.

RESULTS

Most pigs produced for commercial purposes in Sweden are raised without outdoor access. Of the 211 responding pig producers, 80% saw wild boar or signs of wild boar activity in the vicinity of their farm at least once during the year. Observations were significantly correlated with geographical region, but there was no correlation between farm characteristics (farm size, main type of production, outdoor access) and observed wild boar presence or proximity. However, a reported higher frequency of wild boar observations was positively correlated with the observations being made in closer proximity to the farm. Hunting and strategic baiting were the most common mitigation strategies used to keep wild boar at bay. Of the 14 farms raising pigs with outdoor access, 12 responded that these pigs could be raised solely indoors if needed. Pigs with outdoor access are required to be fenced in, but double fencing in these outdoor pig enclosures was not practiced by all. A perimeter fence surrounding any type of pig farm was very rare. More than half of the producers that grew crops with intended use for pigs reported crop damage by wild boar.

CONCLUSION

This study shows that although pigs raised for commercial purposes in Sweden are, to a large extent, kept indoors the potential for indirect contact with wild boar exists and must be considered. Variable local situations regarding wild boar abundance may require an adaptive approach regarding biosecurity efforts.

The role of mucosal barriers in disease progression and transmission

Mucus is a biological hydrogel that coats and protects all non-keratinized wet epithelial surfaces. Mucins, the primary structural components of mucus, are critical components of the gel layer that protect against invading pathogens. For communicable diseases, pathogen-mucin interactions contribute to the pathogen's fate and the potential for disease progression in-host, as well as the potential for onward transmission. We begin by reviewing in-host mucus filtering mechanisms, including size filtering and interaction filtering, which regulate the permeability of mucus barriers to all molecules including pathogens. Next, we discuss the role of mucins in communicable diseases at the point of transmission (i.e. how the encapsulation of pathogens in emitted mucosal droplets externally to hosts may modulate pathogen infectivity and viability). Overall, mucosal barriers modulate both host susceptibility as well as the dynamics of population-level disease transmission. The study of mucins and their use in models and experimental systems are therefore crucial for understanding the mechanistic biophysical principles underlying disease transmission and the early stages of host infection.

The aquaculture disease network model (AquaNet-Mod): A simulation model to evaluate disease spread and controls for the salmonid industry in England and Wales

Infectious disease causes significant mortality in wild and farmed systems, threatening biodiversity, conservation and animal welfare, as well as food security. To mitigate impacts and inform policy, tools such as mathematical models and computer simulations are valuable for predicting the potential spread and impact of disease. This paper describes the development of the Aquaculture Disease Network Model, AquaNet-Mod, and demonstrates its application to evaluating disease epidemics and the efficacy of control, using a Viral Haemorrhagic Septicaemia (VHS) case study. AquaNet-Mod is a data-driven, stochastic, state-transition model. Disease spread can occur via four different mechanisms, i) live fish movement, ii) river based, iii) short distance mechanical and iv) distance independent mechanical. Sites transit between three disease states: susceptible, clinically infected and subclinically infected. Disease spread can be interrupted by the application of disease mitigation measures and controls such as contact tracing, culling, fallowing and surveillance. Results from a VHS case study highlight the potential for VHS to spread to 96% of sites over a 10 year time horizon if no disease controls are applied. Epidemiological impact is significantly reduced when live fish movement restrictions are placed on the most connected sites and further still, when disease controls, representative of current disease control policy in England and Wales, are applied. The importance of specific disease control measures, particularly contact tracing and disease detection rate, are also highlighted. The merit of this model for evaluation of disease spread and the efficacy of controls, in the context of policy, along with potential for further application and development of the model, for example to include economic parameters, is discussed.

Extending EpiEstim to estimate the transmission advantage of pathogen variants in real-time: SARS-CoV-2 as a case-study

The evolution of SARS-CoV-2 has demonstrated that emerging variants can set back the global COVID-19 response. The ability to rapidly assess the threat of new variants is critical for timely optimisation of control strategies. We present a novel method to estimate the effective transmission advantage of a new variant compared to a reference variant combining information across multiple locations and over time. Through an extensive simulation study designed to mimic real-time epidemic contexts, we show that our method performs well across a range of scenarios and provide guidance on its optimal use and interpretation of results. We also provide an open-source software implementation of our method. The computational speed of our tool enables users to rapidly explore spatial and temporal variations in the estimated transmission advantage. We estimate that the SARS-CoV-2 Alpha variant is 1.46 (95% Credible Interval 1.44-1.47) and 1.29 (95% CrI 1.29-1.30) times more transmissible than the wild type, using data from England and France respectively. We further estimate that Delta is 1.77 (95% CrI 1.69-1.85) times more transmissible than Alpha (England data). Our approach can be used as an important first step towards quantifying the threat of emerging or co-circulating variants of infectious pathogens in real-time.

Variation in herbivore space use: comparing two savanna ecosystems with different anthrax outbreak patterns in southern Africa

BACKGROUND

The distribution of resources can affect animal range sizes, which in turn may alter infectious disease dynamics in heterogenous environments. The risk of pathogen exposure or the spatial extent of outbreaks may vary with host range size. This study examined the range sizes of herbivorous anthrax host species in two ecosystems and relationships between spatial movement behavior and patterns of disease outbreaks for a multi-host environmentally transmitted pathogen.

METHODS

We examined range sizes for seven host species and the spatial extent of anthrax outbreaks in Etosha National Park, Namibia and Kruger National Park, South Africa, where the main host species and outbreak sizes differ. We evaluated host range sizes using the local convex hull method at different temporal scales, within-individual temporal range overlap, and relationships between ranging behavior and species contributions to anthrax cases in each park. We estimated the spatial extent of annual anthrax mortalities and evaluated whether the extent was correlated with case numbers of a given host species.

RESULTS

Range size differences among species were not linearly related to anthrax case numbers. In Kruger the main host species had small range sizes and high range overlap, which may heighten exposure when outbreaks occur within their ranges. However, different patterns were observed in Etosha, where the main host species had large range sizes and relatively little overlap. The spatial extent of anthrax mortalities was similar between parks but less variable in Etosha than Kruger. In Kruger outbreaks varied from small local clusters to large areas and the spatial extent correlated with case numbers and species affected. Secondary host species contributed relatively few cases to outbreaks; however, for these species with large range sizes, case numbers positively correlated with outbreak extent.

CONCLUSIONS

Our results provide new information on the spatiotemporal structuring of ranging movements of anthrax host species in two ecosystems. The results linking anthrax dynamics to host space use are correlative, yet suggest that, though partial and proximate, host range size and overlap may be contributing factors in outbreak characteristics for environmentally transmitted pathogens.

Transmission and infection risk of COVID-19 when people coughing in an elevator

People in cities use elevators daily. With the COVID-19 pandemic, there are more worries about elevator safety, since elevators are often small and crowded. This study used a proven CFD model to see how the virus could spread in elevators. We simulated five people taking in an elevator for 2 min and analyzed the effect of different factors on the amount of virus that could be inhaled, such as the infected person's location, the standing positions of the persons, and the air flow rate. We found that the position of the infected person and the direction they stood greatly impacted virus transmission in the elevator. The use of mechanical ventilation with a flow rate of 30 ACH (air changes per hour) was effective in reducing the risk of infection. In situations where the air flow rate was 3 ACH, we found that the highest number of inhaled virus copies could range from 237 to 1186. However, with a flow rate of 30 ACH, the highest number was reduced to 153 to 509. The study also showed that wearing surgical masks decreased the highest number of inhaled virus copies to 74 to 155.

Biowastes of slaughterhouses and wet markets: an overview of waste management for disease prevention

Slaughterhouse and wet market wastes are pollutants that have been always neglected by society. According to the Food and Agriculture Organization of the United Nations, more than three billion and nineteen million livestock were consumed worldwide in 2018, which reflects the vast amount and the broad spectrum of the biowastes generated. Slaughterhouse biowastes are a significant volume of biohazards that poses a high risk of contamination to the environment, an outbreak of diseases, and insecure food safety. This work comprehensively reviewed existing biowaste disposal practices and revealed the limitations of technological advancements to eradicate the threat of possible harmful infectious agents from these wastes. Policies, including strict supervision and uniform minimum hygienic regulations at all raw food processing factories, should therefore be tightened to ensure the protection of the food supply. The vast quantity of biowastes also offers a zero-waste potential for a circular economy, but the incorporation of biowaste recycling, including composting, anaerobic digestion, and thermal treatment, nevertheless remains challenging.

Occurrence and limited zoonotic potential of Cryptosporidium spp., Giardia duodenalis, and Balantioides coli infections in free-ranging and farmed wild ungulates in Spain

Little information is currently available on the occurrence and molecular diversity of the enteric protozoan parasites Cryptosporidium spp., Giardia duodenalis, and Balantioides coli in wild ungulates and the role of these host species as potential sources of environmental contamination and consequent human infections. The presence of these three pathogens was investigated in eight wild ungulate species present in Spain (genera Ammotragus, Capra, Capreolus, Cervus, Dama, Ovis, Rupicapra, and Sus) by molecular methods. Faecal samples were retrospectively collected from free-ranging (n = 1058) and farmed (n = 324) wild ungulates from the five Spanish bioregions. Overall infection rates were 3.0% (42/1382; 95% CI: 2.1-3.9%) for Cryptosporidium spp., 5.4% (74/1382; 95% CI: 4.2-6.5%) for G. duodenalis, and 0.7% (9/1382; 95% CI: 0.3-1.2%) for B. coli. Cryptosporidium infection was detected in roe deer (7.5%), wild boar (7.0%) and red deer (1.5%), and G. duodenalis in southern chamois (12.9%), mouflon (10.0%), Iberian wild goat (9.0%), roe deer (7.5%), wild boar (5.6%), fallow deer (5.2%) and red deer (3.8%). Balantioides coli was only detected in wild boar (2.5%, 9/359). Sequence analyses revealed the presence of six distinct Cryptosporidium species: C. ryanae in red deer, roe deer, and wild boar; C. parvum in red deer and wild boar; C. ubiquitum in roe deer; C. scrofarum in wild boar; C. canis in roe deer; and C. suis in red deer. Zoonotic assemblages A and B were detected in wild boar and red deer, respectively. Ungulate-adapted assemblage E was identified in mouflon, red deer, and southern chamois. Attempts to genotype samples positive for B. coli failed. Sporadic infections by canine- or swine-adapted species may be indicative of potential cross-species transmission, although spurious infections cannot be ruled out. Molecular evidence gathered is consistent with parasite mild infections and limited environmental contamination with (oo)cysts. Free-ranging wild ungulate species would not presumably play a significant role as source of human infections by these pathogens. Wild ruminants do not seem to be susceptible hosts for B. coli.

Descriptive network analysis and the influence of timescale on centrality and cohesion metrics from a system of between-herd dairy cow movements in Ontario, Canada

Previous research has demonstrated that static monthly networks of between-herd dairy cow movements in Ontario, Canada were highly fragmented, reducing potential for large-scale outbreaks. Extrapolating results from static networks can become problematic for diseases with an incubation period that exceeds the timescale of the network. The objectives of this research were to: 1) describe the networks of dairy cow movements in Ontario, and 2) describe the changes that occur among network analysis metrics when conducted at seven different timescales. Networks of dairy cow movements were created using Lactanet Canada milk recording data collected in Ontario between 2009 and 2018. Centrality and cohesion metrics were calculated after aggregating the data at seven timescales: weekly, monthly, semi-annual, annual, biennial, quinquennial, and decennial. There were 50,598 individual cows moved between Lactanet-enrolled farms, representing approximately 75% of provincially registered dairy herds. Most movements occurred over short distances (median = 39.18 km), with fewer long-range movements (maximum = 1150.80 km). The number of arcs increased marginally relative to the number of nodes with longer network timescales. Both mean out-degree, and mean clustering coefficients increased disproportionately with increasing timescale. Conversely, mean network density decreased with increasing timescale. The largest weak and strong components at the monthly timescale were small relative to the full network (267 and 4 nodes), whereas yearly networks had much higher values (2213 and 111 nodes). Higher relative connectivity in networks with longer timescales suggests pathogens with long incubation periods and animals with subclinical infection present increased potential for wide-spread disease transmission among dairy farms in Ontario. Careful consideration of disease-specific dynamics should be made when using static networks to model disease transmission among dairy cow populations.

Revisiting classical SIR modelling in light of the COVID-19 pandemic

Background

Classical infectious disease models during epidemics have widespread usage, from predicting the probability of new infections to developing vaccination plans for informing policy decisions and public health responses. However, it is important to correctly classify reported data and understand how this impacts estimation of model parameters. The COVID-19 pandemic has provided an abundant amount of data that allow for thorough testing of disease modelling assumptions, as well as how we think about classical infectious disease modelling paradigms.

Objective

We aim to assess the appropriateness of model parameter estimates and prediction results in classical infectious disease compartmental modelling frameworks given available data types (infected, active, quarantined, and recovered cases) for situations where just one data type is available to fit the model. Our main focus is on how model prediction results are dependent on data being assigned to the right model compartment.

Methods

We first use simulated data to explore parameter reliability and prediction capability with three formulations of the classical Susceptible-Infected-Removed (SIR) modelling framework. We then explore two applications with reported data to assess which data and models are sufficient for reliable model parameter estimation and prediction accuracy: a classical influenza outbreak in a boarding school in England and COVID-19 data from the fall of 2020 in Missoula County, Montana, USA.

Results

We demonstrated the magnitude of parameter estimation errors and subsequent prediction errors resulting from data misclassification to model compartments with simulated data. We showed that prediction accuracy in each formulation of the classical disease modelling framework was largely determined by correct data classification versus misclassification. Using a classical example of influenza epidemics in an England boarding school, we argue that the Susceptible-Infected-Quarantined-Recovered (SIQR) model is more appropriate than the commonly employed SIR model given the data collected (number of active cases). Similarly, we show in the COVID-19 disease model example that reported active cases could be used inappropriately in the SIR modelling framework if treated as infected.

Conclusions

We demonstrate the role of misclassification of disease data and thus the importance of correctly classifying reported data to the proper compartment using both simulated and real data. For both a classical influenza data set and a COVID-19 case data set, we demonstrate the implications of using the "right" data in the "wrong" model. The importance of correctly classifying reported data will have downstream impacts on predictions of number of infections, as well as minimal vaccination requirements.

The effect of changing COVID-19 restrictions on the transmission rate in a veterinary clinic

With the declaration of the COVID-19 pandemic by the World Health Organization on March 11, 2020, the University of Tennessee College of Veterinary Medicine (UTCVM), like other institutions, restructured their services to reduce the potential spread of the COVID-19 virus while simultaneously providing critical and essential veterinary services. A mathematical model was developed to predict the change in the level of possible COVID-19 infections due to the increased number of potential contacts within the UTCVM hospital. A system of ordinary differential equations with different compartments for UTCVM individuals and the Knox county population was formulated to show the dynamics of transmission and the number of confirmed cases. Key transmission rates in the model were estimated using COVID-19 case data from the surrounding county and UTCVM personnel. Simulations from this model show the increasing number of COVID-19 cases among UTCVM personnel as the number of daily clients and the number of veterinary staff in the clinic are increased. We also investigate how changes within the Knox county community impact the UTCVM hospital. These scenarios show the importance of understanding the effects of re-opening scenarios in veterinary teaching hospitals.

Emergency department presentations during the COVID-19 pandemic in Queensland (to June 2021): interrupted time series analysis

OBJECTIVES

To assess emergency department (ED) presentation numbers in Queensland during the coronavirus disease 2019 (COVID-19) pandemic to mid-2021, a period of relatively low COVID-19 case numbers.

DESIGN

Interrupted time series analysis.

SETTING

All 105 Queensland public hospital EDs.

MAIN OUTCOME MEASURES

Numbers of ED presentations during the COVID-19 lockdown period (11 March 2020 - 30 June 2020) and the period of easing restrictions (1 July 2020 - 30 June 2021), compared with pre-pandemic period (1 January 2018 - 10 March 2020), overall (daily numbers) and by Australasian Triage Scale (ATS; daily numbers) and selected diagnostic categories (cardiac, respiratory, mental health, injury-related conditions) and conditions (stroke, sepsis) (weekly numbers).

RESULTS

During the lockdown period, the mean number of ED presentations was 19.4% lower (95% confidence interval, -20.9% to -17.9%) than during the pre-pandemic period (predicted mean number: 5935; actual number: 4786 presentations). The magnitudes of the decline and the time to return to predicted levels varied by ATS category and diagnostic group; changes in presentation numbers were least marked for ATS 1 and 2 (most urgent) presentations, and for presentations with cardiac conditions or stroke. Numbers remained below predicted levels during the 12-month post-lockdown period for ATS 5 (least urgent) presentations and presentations with mental health problems, respiratory conditions, or sepsis.

CONCLUSIONS

The COVID-19 pandemic and related public restrictions were associated with profound changes in health care use. Pandemic plans should include advice about continuing to seek care for serious health conditions and health emergencies, and support alternative sources of care for less urgent health care needs.

Conversational head movement decreases close-contact exposure to expired respiratory droplets

People constantly move their heads during conversation, as such movement is an important non-verbal mode of communication. Head movement alters the direction of people's expired air flow, therefore affecting their conversational partners' level of exposure. Nevertheless, there is a lack of understanding of the mechanism whereby head movement affects people's exposure. In this study, a dynamic meshing method in computational fluid dynamics was used to simulate the head movement of a human-shaped thermal manikin. Droplets were released during the oral expiration periods of the source manikin, during which it was either motionless, was shaking its head or was nodding its head, while the head of a face-to-face target manikin remained motionless. The results indicate that the target manikin had a high level of exposure to respiratory droplets when the source manikin was motionless, whereas the target manikin's level of exposure was significantly reduced when the source manikin was shaking or nodding its head. The source manikin had the highest level of self-exposure when it was nodding its head and the lowest level of self-exposure when its head was motionless. People's level of exposure during close contact is highly variable, highlighting the need for further investigations in more realistic conversational scenarios.

Multisectoral Perspectives on Global Warming and Vector-borne Diseases: a Focus on Southern Europe

Purpose of Review

The climate change (CC) or global warming (GW) modifies environment that favors vectors' abundance, growth, and reproduction, and consequently, the rate of development of pathogens within the vectors. This review highlights the threats of GW-induced vector-borne diseases (VBDs) in Southern Europe (SE) and the need for mitigation efforts to prevent potential global health catastrophe.

Recent Findings

Reports showed astronomical surges in the incidences of CC-induced VBDs in the SE. The recently (2022) reported first cases of African swine fever in Northern Italy and West Nile fever in SE are linked to the CC-modified environmental conditions that support vectors and pathogens' growth and development, and disease transmission.

Summary

VBDs endemic to the tropics are increasingly becoming a major health challenge in the SE, a temperate region, due to the favorable environmental conditions caused by CC/GW that support vectors and pathogens' biology in the previously non-endemic temperate regions.

Effects of classroom cleaning on student health: a longitudinal study

BACKGROUND

School districts across the world have been grappling with how to keep their schools open, students healthy, and prevent the spread of viruses in their communities.

OBJECTIVE

The aims of this study included assessing both (1) the effectiveness of enhanced classroom cleaning and disinfecting protocol on surface biocontamination and (2) the associations between surface biocontamination and student absence due to illnesses.

METHODS

Cleaning effectiveness was assessed using quantitative adenosine triphosphate (ATP) measurements during a 10-week study period in a sample of 34 public schools (15,814 students), of a district located in the Western US. The schools were randomly assigned to 17 intervention schools implementing enhanced cleaning and disinfecting protocol and 17 control schools cleaning as usual. General estimating equations (GEEs) were used for modeling associations between ATP levels and weekly aggregates of student absences due to respiratory and gastrointestinal illnesses, which were recorded by the schools according to district wide protocol.

RESULTS

The weekly average ATP levels on logarithmic scale were 5.02 (SD 0.53) and 5.26 (SD 0.48) in the intervention and control schools, respectively, where the difference is statistically significant (p < 0.001). The probability of weekly absence due to gastrointestinal illness was significantly associated with ATP levels (parameter estimate 1.16, 95% CI 1.01-1.34, per unit (log) increase of weekly average ATP), where the model accounts for student level, gender, ethnic group, and socioeconomic status as well as for school level attendance, total absence ratio, and ventilation adequacy in classrooms. Associations were not found between ATP levels and weekly probability of any absence, or absence due to respiratory illness.

SIGNIFICANCE

Enhanced cleaning resulted in a significantly lower level of biocontamination on desktops in the intervention group. In addition, a statistically significant association was established between ATP levels on classroom desks and probability of absence due to gastrointestinal illness.

IMPACT

We found that enhanced cleaning protocol, including bi-weekly cleaning of classroom desks, as well as training of custodians and teachers, monitoring of effectiveness, and feedback, yielded a moderate but statistically significantly lower level of biocontamination on desktops, indicated by quantitative ATP monitoring. Within the range of weekly average desktop ATP levels observed, the probability of reported absence due to gastrointestinal illness is estimated to increase from 0.021 to 0.026. Based on the results, enhanced surface cleaning and monitoring its effectiveness is a possible district, state, or even national level policy to support healthy school environments.

Impact of pre-pandemic travel mobility patterns on the spatial diffusion of COVID-19 in South Korea

Introduction

Physical mobility is critical for the spread of infectious diseases in humans. However, few studies have conducted empirical investigations on the impact of pre-pandemic travel mobility patterns on the diffusion of coronavirus disease 2019 (COVID-19). Therefore, this study examines its impact at the city-county level on the diffusion by the wave period during the two-year pandemic in South Korea.

Methods

This study first employs factor analysis by using the travel origin-destination data by travel mode at the county level as of 2019 to derive pre-pandemic travel mobility patterns. Next, the study identifies how they had affected the diffusion of COVID-19 over time by employing the negative binomial regression models on confirmed COVID-19 cases for each wave, including the entire pandemic period.

Results

The study derived five pre-pandemic mobility patterns: 1) rail-oriented mobility, 2) intra-county bus-oriented mobility, 3) road-oriented mobility, 4) high-speed rail-oriented mobility, and 5) inter-county bus-oriented mobility. Among them, the biggest risk to the diffusion of COVID-19 was the rail-oriented mobility before the pandemic if controlling such measures as accessibility, physical environment, and demographic and socioeconomic indicators. In addition, the order of the magnitudes for the impact of pre-pandemic travel mobility factors on its spatial diffusion had not changed during experiencing the three different wave periods during the two-year pandemic in South Korea.

Conclusions

The study concludes that the rail-oriented travel mobility pattern before the pandemic could pose the greatest threat factor to the spatial spread of COVID-19 at any scale and time. Policymakers should develop strategies to prevent the spatial spread of COVID-19 by reducing human mobility for daily living in areas with strong rail mobility patterns formed before the pandemic.

SARS-CoV-2 in a tropical area of Colombia, a remarkable conversion of presymptomatic to symptomatic people impacts public health

Background

The ability of SARS-CoV-2 to remain in asymptomatic individuals facilitates its dissemination and makes its control difficult. Objective. To establish a cohort of asymptomatic individuals, change to the symptomatic status, and determine the most frequent clinical manifestations. 

Methods

Between April 9 and August 9, 2020, molecular diagnosis of SARS-CoV-2 infection was confirmed in 154 asymptomatic people in contact with subjects diagnosed with COVID-19. Nasopharyngeal swabs were performed on these people in different hospitals in Córdoba, the Caribbean area of Colombia. The genes E, RdRp, and N were amplified with RT-qPCR. Based on the molecular results and the Cq values, the patients were subsequently followed up through telephone calls to verify their health conditions.

Results

Overall, of 154 asymptomatic individuals, 103 (66.9%) remained asymptomatic, and 51 (33.1%) changed to symptomatic. The most frequent clinical manifestations in young people were anosmia and arthralgia. Adults showed cough, ageusia, and odynophagia; in the elderly were epigastralgia, dyspnea, and headache. Mortality was 8%.

Conclusions

A proportion of 33% of presymptomatic individuals was found, of which four of them died. This high rate could indicate a silent transmission, contributing significantly to the epidemic associated with SARS-CoV-2.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07575-0.

A framework for integrating inferred movement behavior into disease risk models

Movement behavior is an important contributor to habitat selection and its incorporation in disease risk models has been somewhat neglected. The habitat preferences of host individuals affect their probability of exposure to pathogens. If preference behavior can be incorporated in ecological niche models (ENMs) when data on pathogen distributions are available, then variation in such behavior may dramatically impact exposure risk. Here we use data from the anthrax endemic system of Etosha National Park, Namibia, to demonstrate how integrating inferred movement behavior alters the construction of disease risk maps. We used a Maximum Entropy (MaxEnt) model that associated soil, bioclimatic, and vegetation variables with the best available pathogen presence data collected at anthrax carcass sites to map areas of most likely Bacillus anthracis (the causative bacterium of anthrax) persistence. We then used a hidden Markov model (HMM) to distinguish foraging and non-foraging behavioral states along the movement tracks of nine zebra (Equus quagga) during the 2009 and 2010 anthrax seasons. The resulting tracks, decomposed on the basis of the inferred behavioral state, formed the basis of step-selection functions (SSFs) that used the MaxEnt output as a potential predictor variable. Our analyses revealed different risks of exposure during different zebra behavioral states, which were obscured when the full movement tracks were analyzed without consideration of the underlying behavioral states of individuals. Pathogen (or vector) distribution models may be misleading with regard to the actual risk faced by host animal populations when specific behavioral states are not explicitly accounted for in selection analyses. To more accurately evaluate exposure risk, especially in the case of environmentally transmitted pathogens, selection functions could be built for each identified behavioral state and then used to assess the comparative exposure risk across relevant states. The scale of data collection and analysis, however, introduces complexities and limitations for consideration when interpreting results.

Understanding Sabiá virus infections (Brazilian mammarenavirus)

BACKGROUND

Only two naturally occurring human Sabiá virus (SABV) infections have been reported, and those occurred over 20 years ago.

METHODS

We diagnosed two new cases of SABV infection using metagenomics in patients thought to have severe yellow fever and described new features of histopathological findings.

RESULTS

We characterized clinical manifestations, histopathology and analyzed possible nosocomial transmission. Patients presented with hepatitis, bleeding, neurological alterations and died. We traced twenty-nine hospital contacts and evaluated them clinically and by RT-PCR and neutralizing antibodies. Autopsies uncovered unique features on electron microscopy, such as hepatocyte "pinewood knot" lesions. Although previous reports with similar New-World arenavirus had nosocomial transmission, our data did not find any case in contact tracing.

CONCLUSIONS

Although an apparent by rare, Brazilian mammarenavirus infection is an etiology for acute hemorrhagic fever syndrome. The two fatal cases had peculiar histopathological findings not previously described. The virological diagnosis was possible only by contemporary techniques such as metagenomic assays. We found no subsequent infections when we used serological and molecular tests to evaluate close contacts.

Examining the role of person-to-person transmission during a verocytotoxigenic Escherichia coli outbreak in Ontario, Canada

OBJECTIVE

Person-to-person transmission can occur during outbreaks of verotoxigenic Escherichia coli (VTEC), however the impact of this transmission route is not well understood. This study aimed to examine the role of person-to-person transmission during a VTEC outbreak, and how targeting this route may reduce outbreak size. A deterministic compartmental model describing a VTEC outbreak was constructed and fit to data from a 2008 outbreak in Ontario, Canada. Using the best-fit model, simulations were run to calculate the: reduction in transmission rate after implementing interventions, proportion of cases infected through both transmission routes, and number of cases prevented by interventions. Latin hypercube sensitivity analysis was conducted to examine the sensitivity of the outbreak size to the model parameters.

RESULTS

Based on the best-fit model, ~ 14.25% of the cases likely arose due to person-to-person transmission. Interventions reduced this transmission rate by ~ 73%, causing a reduction in outbreak size of ~ 17% (47 cases). Sensitivity analysis showed that the model was highly sensitive to changes in all parameters of the model. The model demonstrates that person-to-person could be an important transmission route during VTEC outbreaks. Targeting this route of transmission through hand hygiene and work exclusions could reduce the final outbreak size.

On male urination and related environmental disease transmission in restrooms: From the perspectives of fluid dynamics

Indoor transmission of COVID-19 is highly probable. Multiple sources have verified that the SARS-CoV-2 can be detected within toilets, and people can be infected in restrooms. There is a huge gap in the coronavirus transmission mechanism in restrooms. Understanding it can help to flatten the curve of the infected cases as well as prevent other viruses transmitted through the sewage or human body fluid. Previous studies have shown how simple actions in daily life (coughing, sneezing, or toilet flushing) contribute to virus transmission. This paper visually and quantitatively demonstrates that male urination, which is also a daily action, can agitate virus particles within the toilet and raise them, which may be the main promoter of cross-infection of COVID-19 in restrooms. Adopting numerical and experimental methods, we demonstrate that male urination can cause strong turbulent flow with an averaged urine impinging velocity of 2.3 m/s, which can act as an agitator to raise the virus particles. The climbing velocity of the airflow can be 0.75-1.05 m/s. The observed upwards flow will disturb and spread any lurking virus particles (not limited to SARS-CoV-2). Experiments demonstrated that the concentration of the airborne particle could be tripled during male urination. Corresponding precautions are offered as well to prepare the public to act properly when and after using facilities in restrooms for preventing emerging and re-emerging pandemics not limited to the current COVID-19, contributing to the sustainability of human society.

Risk assessment of hepatitis E transmission through tissue allografts

Hepatitis E virus (HEV) is a small non-enveloped single stranded RNA virus whose genotypes 3 and 4 have been associated with zoonotic transmission in industrialized countries. HEV infection is considered the main cause of acute hepatitis worldwide. In some cases, transfusion of blood components or organ transplantation have been reported as the source of infection. We have conducted a literature review on the risk of transmission through cell and tissue allografts. Although no case was found, measures to control this risk should be taken when donor profile (based upon geographical and behavioural data) recommended it. Issues to be considered in donor screening and tissue processing to assess and to reduce the risk of HEV transmission are approached.

Investigating the association between mass transit adoption and COVID-19 infections in US metropolitan areas

Urbanization introduces the threat of increased epidemic disease transmission resulting from crowding on mass transit. The coronavirus disease 2019 (COVID-19) pandemic, which has directly led to over 600,000 deaths in the US as of July 2021, triggered mass social distancing policies to be enacted as a key deterrent of widespread infections. Social distancing can be challenging in confined spaces required for transportation such as mass transit systems. Little is published regarding the degree to which mass transit system adoption effects impacted the rise of the COVID-19 pandemic in urban centers. Taking an ecological approach where areal data are the unit of observation, this national-scale study aims to measure the association between the adoption of mass transit and COVID-19 spread through confirmed cases in US metropolitan areas. National survey-based transit adoption measures are entered in negative binomial regression models to evaluate differences between areas. The model results demonstrate that mass transit adoption in US metropolitan areas was associated with the magnitude of outbreaks. Higher incidence of COVID-19 early in the pandemic was associated with survey results conveying higher transit use. Increasing weekly bus transit usage in metropolitan statistical areas by one scaled unit was associated with a 1.38 [95% CI: (1.25, 1.90)] times increase in incidence rate of COVID-19; a one scaled unit increase in weekly train transit usage was associated with an increase in incidence rate of 1.54 [95% CI: (1.42, 2.07)] times. These conclusions should inform early action practices in urban centers with busy transit systems in the event of future infectious disease outbreaks. Deeper understanding of these observed associations may also benefit modeling efforts by allowing researchers to include mathematical adjustments or better explain caveats to results when communicating with decision makers and the public in the crucial early stages of an epidemic.

Quarantine and testing strategies to ameliorate transmission due to travel during the COVID-19 pandemic: a modelling study

BACKGROUND

Numerous countries have imposed strict travel restrictions during the COVID-19 pandemic, contributing to a large socioeconomic burden. The long quarantines that have been applied to contacts of cases may be excessive for travel policy.

METHODS

We developed an approach to evaluate imminent countrywide COVID-19 infections after 0-14-day quarantine and testing. We identified the minimum travel quarantine duration such that the infection rate within the destination country did not increase compared to a travel ban, defining this minimum quarantine as "sufficient."

FINDINGS

We present a generalised analytical framework and a specific case study of the epidemic situation on November 21, 2021, for application to 26 European countries. For most origin-destination country pairs, a three-day or shorter quarantine with RT-PCR or antigen testing on exit suffices. Adaptation to the European Union traffic-light risk stratification provided a simplified policy tool. Our analytical approach provides guidance for travel policy during all phases of pandemic diseases.

INTERPRETATION

For nearly half of origin-destination country pairs analysed, travel can be permitted in the absence of quarantine and testing. For the majority of pairs requiring controls, a short quarantine with testing could be as effective as a complete travel ban. The estimated travel quarantine durations are substantially shorter than those specified for traced contacts.

FUNDING

EasyJet (JPT and APG), the Elihu endowment (JPT), the Burnett and Stender families' endowment (APG), the Notsew Orm Sands Foundation (JPT and APG), the National Institutes of Health (MCF), Canadian Institutes of Health Research (SMM) and Natural Sciences and Engineering Research Council of Canada EIDM-MfPH (SMM).

The impact of re-opening the international border on COVID-19 hospitalisations in Australia: a modelling study

OBJECTIVE

To estimate the numbers of COVID-19-related hospitalisations in Australia after re-opening the international border.

DESIGN

Population-level deterministic compartmental epidemic modelling of eight scenarios applying various assumptions regarding SARS-CoV-2 transmissibility (baseline R0 = 3.5 or 7.0), vaccine rollout speed (slow or fast), and scale of border re-opening (mean of 2500 or 13 000 overseas arrivals per day).

SETTING

Simulation population size, age structure, and age-based contact rates based on recent estimates for the Australian population. We assumed that 80% vaccination coverage of people aged 16 years or more was reached in mid-October 2021 (fast rollout) or early January 2022 (slow rollout).

MAIN OUTCOME MEASURES

Numbers of people admitted to hospital with COVID-19, December 2021 - December 2022.

RESULTS

In scenarios assuming a highly transmissible SARS-CoV-2 variant (R0  = 7.0), opening the international border on either scale was followed by surges in both infections and hospitalisations that would require public health measures beyond mask wearing and social distancing to avoid overwhelming the health system. Reducing the number of hospitalisations to manageable levels required several cycles of additional social and mobility restrictions.

CONCLUSIONS

If highly transmissible SARS-CoV-2 variants are circulating locally or overseas, large and disruptive COVID-19 outbreaks will still be possible in Australia after 80% of people aged 16 years or more have been vaccinated. Continuing public health measures to restrict the spread of disease are likely to be necessary throughout 2022.

Wild boar visits to commercial pig farms in southwest England: implications for disease transmission

Contact between wild animals and farmed livestock may result in disease transmission with huge financial, welfare and ethical consequences. Conflicts between people and wildlife can also arise when species such as wild boar (Sus scrofa) consume crops or dig up pasture. This is a relatively recent problem in England where wild boar populations have become re-established in the last 20 years following a 500-year absence. The aim of this pilot study was to determine if and how often free-living wild boar visited two commercial pig farms near the Forest of Dean in southwest England. We placed 20 motion-sensitive camera traps at potential entry points to, and trails surrounding, the perimeter of two farmyards housing domestic pigs between August 2019 and February 2021, covering a total of 6030 trap nights. Forty wild boar detections were recorded on one farm spread across 27 nights, with a median (range) of 1 (0 to 7) night of wild boar activity per calendar month. Most of these wild boar detections occurred between ten and twenty metres of housed domestic pigs. No wild boar was detected at the other farm. These results confirm wild boar do visit commercial pig farms, and therefore, there is potential for contact and pathogen exchange between wild boar and domestic pigs. The visitation rates derived from this study could be used to parameterise disease transmission models of pathogens common to domestic pigs and wild boars, such as the African swine fever virus, and subsequently to develop mitigation strategies to reduce unwanted contacts.

Increasing concentration of COVID-19 by socioeconomic determinants and geography in Toronto, Canada: an observational study

BACKGROUND

Inequities in the burden of COVID-19 were observed early in Canada and around the world, suggesting economically marginalized communities faced disproportionate risks. However, there has been limited systematic assessment of how heterogeneity in risks has evolved in large urban centers over time.

PURPOSE

To address this gap, we quantified the magnitude of risk heterogeneity in Toronto, Ontario from January to November 2020 using a retrospective, population-based observational study using surveillance data.

METHODS

We generated epidemic curves by social determinants of health (SDOH) and crude Lorenz curves by neighbourhoods to visualize inequities in the distribution of COVID-19 and estimated Gini coefficients. We examined the correlation between SDOH using Pearson-correlation coefficients.

RESULTS

Gini coefficient of cumulative cases by population size was 0.41 (95% confidence interval [CI]:0.36-0.47) and estimated for: household income (0.20, 95%CI: 0.14-0.28); visible minority (0.21, 95%CI:0.16-0.28); recent immigration (0.12, 95%CI:0.09-0.16); suitable housing (0.21, 95%CI:0.14-0.30); multigenerational households (0.19, 95%CI:0.15-0.23); and essential workers (0.28, 95%CI:0.23-0.34).

CONCLUSIONS

There was rapid epidemiologic transition from higher- to lower-income neighborhoods with Lorenz curve transitioning from below to above the line of equality across SDOH. Moving forward necessitates integrating programs and policies addressing socioeconomic inequities and structural racism into COVID-19 prevention and vaccination programs.

How territoriality reduces disease transmission among social insect colonies

Abstract

Social behavior can have a major impact on the dynamics of infectious disease outbreaks. For animals that live in dense social groups, such as the eusocial insects, pathogens pose an especially large risk because frequent contacts among individuals can allow rapid spread within colonies. While there has been a large body of work examining adaptations to mitigate the spread of infectious disease within social insect colonies, there has been less work on strategies to prevent the introduction of pathogens into colonies in the first place. We develop an agent-based model to examine the effect of territorial behavior on the transmission of infectious diseases between social insect colonies. We find that by preventing the introduction of infected foreign workers into a colony, territoriality can flatten the curve of an epidemic, delaying the introduction of an infectious disease and reducing its maximum prevalence, but only for diseases with moderate to low transmissibility. Our results have implications for understanding how pathogen risk influences the evolution of territorial behavior in social insects and other highly social animals.

Significance statement

Infectious disease outbreaks can impose a large fitness cost to animals that live in social groups. The frequency and pattern of contacts both within and among groups can have a large impact on the speed and extent of an epidemic. Using an individual-based model, we examined how the exclusion of foreign workers from a territory around the nest influences disease transmission between social insect colonies. We find that territoriality can protect colonies from outbreaks of low to moderately contagious pathogens by delaying the spillover from other colonies and reducing the maximum number of workers who are infected. These results suggest that the relative threat posed by infectious diseases may have played an important role in shaping the diversity of territorial behaviors seen in different social insect species.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00265-021-03095-0.

A mathematical model of COVID-19 transmission

Disease transmission is studied through disciplines like epidemiology, applied mathematics, and statistics. Mathematical simulation models for transmission have implications in solving public and personal health challenges. The SIR model uses a compartmental approach including dynamic and nonlinear behavior of transmission through three factors: susceptible, infected, and removed (recovered and deceased) individuals. Using the Lambert W Function, we propose a framework to study solutions of the SIR model. This demonstrates the applications of COVID-19 transmission data to model the spread of a real-world disease. Different models of disease including the SIR, SIRmp and SEIRρqr model are compared with respect to their ability to predict disease spread. Physical distancing impacts and personal protection equipment use are discussed with relevance to the COVID-19 spread.

Development of a critical appraisal tool for models predicting the impact of 'test, trace, and protect' programmes on COVID-19 transmission

OBJECTIVES

To develop a critical appraisal tool for non-computational-specialist public health professionals to assess the quality and relevance of modelling studies about Test and Trace (and Protect - TTP) programmes' impact on COVID-19 transmission.

STUDY DESIGN

Decision-making tool development.

METHODS

Using Tugwell et al.'s 1985 Health Care Effectiveness equation as a conceptual framework, combined with a purposive search of the relevant early modeling literature, we developed six critical appraisal questions for the rapid assessment of modeling studies related to the evaluation of TTP programmes' effectiveness.

RESULTS

By applying the critical appraisal tool to selected recent COVID-19 modeling studies, we demonstrate how models can be evaluated using the six questions to evaluate internal and external validity and relevance.

CONCLUSIONS

These six critical appraisal questions are able to discriminate between modeling studies of higher and lower quality and relevance to evaluating TTP programmes' impact. However, these questions require independent validation in a larger and systematic sample of relevant modeling studies which have appeared in later stages of the pandemic.

Review: Livestock disease resilience: from individual to herd level

Infectious diseases are a major threat to the sustainable production of high-producing animals. Control efforts, such as vaccination or breeding approaches often target improvements to individual resilience to infections, i.e., they strengthen an animal's ability to cope with infection, rather than preventing infection per se. There is increasing evidence for the contribution of non-clinical carriers (animals that become infected and are infectious but do not develop clinical signs) to the overall health and production of livestock populations for a wide range of infectious diseases. Therefore, we strongly advocate a shift of focus from increasing the disease resilience of individual animals to herd disease resilience as the appropriate target for sustainable disease control in livestock. Herd disease resilience not only captures the direct effects of vaccination or host genetics on the health and production performance of individuals but also the indirect effects on the environmental pathogen load that herd members are exposed to. For diseases primarily caused by infectious pathogens shed by herd members, these indirect effects on herd resilience are mediated both by individual susceptibility to infection and by characteristics (magnitude of infectiousness, duration of infectious period) that influence pathogen shedding from infected individuals. We review what is currently known about how vaccination and selective breeding affect herd disease resilience and its underlying components, and outline the changes required for improvement. To this purpose, we also seek to clarify and harmonise the terminology used in the different animal science disciplines to facilitate future collaborative approaches to infectious disease control in livestock.

Transmission rates and environmental reservoirs for COVID-19 - a modeling study

The coronavirus disease 2019 (COVID-19) remains a global pandemic at present. Although the human-to-human transmission route for this disease has been well established, its transmission mechanism is not fully understood. In this paper, we propose a mathematical model for COVID-19 which incorporates multiple transmission pathways and which employs time-dependent transmission rates reflecting the impact of disease prevalence and outbreak control. Applying this model to a retrospective study based on publicly reported data in China, we argue that the environmental reservoirs play an important role in the transmission and spread of the coronavirus. This argument is supported by our data fitting and numerical simulation results for the city of Wuhan, for the provinces of Hubei and Guangdong, and for the entire country of China.

Unravelling direct and indirect contact patterns between duck farms in France and their association with the 2016-2017 epidemic of Highly Pathogenic Avian Influenza (H5N8)

Live animal movements generate direct contacts (via the exchange of live animals) and indirect contacts (via the transit of transport vehicles) between farms, which can contribute to the spread of pathogens. However, most analyses focus solely on direct contacts and can therefore underestimate the contribution of live animal movements in the spread of infectious diseases. Here, we used French live duck movement data (2016-2018) from one of the largest transport companies to compare direct and indirect contact patterns between duck farms and evaluate how these patterns were associated with the French 2016-2017 epidemic of highly pathogenic avian influenza H5N8. A total number of 614 farms were included in the study, and two directed networks were generated: the animal introduction network (exchange of live ducks) and the transit network (transit of transport vehicles). Following descriptive analyses, these two networks were scrutinized in relation to farm infection status during the epidemic. Results showed that farms were substantially more connected in the transit network than in the animal introduction network and that the transit of transport vehicles generated more opportunities for transmission than the exchange of live animals. We also showed that animal introduction and transit networks' statistics decreased substantially during the epidemic (January-March 2017) compared to non-epidemic periods (January-March 2016 and January-March 2018). We estimated a probability of 33.3 % that a farm exposed to the infection through either of the two live duck movement networks (i.e. that was in direct or indirect contact with a farm that was reported as infected in the following seven days) becomes infected within seven days after the contact. However, we also demonstrated that the level of exposure of farms by these two contact patterns was low, leading only to a handful of transmission events through these routes. As a consequence, we showed that live animal movement patterns are efficient transmission routes for HPAI but have been efficiently reduced to limit the spread during the French 2020-2021 epidemic. These results underpin the relevance of studying indirect contacts resulting from the movement of animals to understand their transmission potential and the importance of accounting for both routes when designing disease control strategies.

Does breastfeeding protect children from COVID-19? An observational study from pediatric services in Majorca, Spain

BACKGROUND

It has been demonstrated that children who had been breastfed remain better protected against various infections, and notably respiratory tract infections, well beyond infancy. Since the role of breastfeeding to explain why children are less affected by COVID-19 has not been studied until now, the aim of this study was to determine whether any history of breastfeeding reduces the incidence rate of COVID-19 in children.

METHODS

This was a secondary analysis of an observational study on clinical and epidemiological characteristics of pediatric COVID-19 in Majorca. A total of 691 children were recruited during the 5 months of August-December 2020. Eligible participants were children under 14 who were tested for SARS-CoV-2 in pediatric emergency services. The independent explanatory variable was any breastfeeding. Bivariate analyses were conducted through the Chi-square test, the Fisher's Exact test or the Student's T test. All children had the same demographic, epidemiological and clinical data collected through a study team member interview and via the participants medical records.

RESULTS

Within the sample of children who visited emergency services with symptoms of potential COVID-19, we found higher prevalence of positive SARS-CoV-2 RT-PCR test results among those who were exclusively formula fed compared with those who were ever breastfed (OR 2.48; 95% CI 1.45, 3.51; P = 0.036).

CONCLUSIONS

The present study suggests that ever breastfeeding reduces the risk of COVID-19 among children, as documented for other infections.

Assessing potential routes of Streptococcus agalactiae transmission between dairy herds using national surveillance, animal movement data and molecular typing

Streptococcus agalactiae, also known as group B Streptococcus (GBS), is a pathogen of humans and animals. It is an important cause of mastitis in dairy cattle, causing decreased milk quality and quantity. Denmark is the only country to have implemented a national surveillance and control campaign for GBS in dairy cattle. After a significant decline in the 20th century, prevalence has increased in the 21st century. Using a unique combination of national surveillance, cattle movement data and molecular typing, we tested the hypothesis that transmission mechanisms differ between GBS strains that are almost exclusive to cattle and those that affect humans as well as cattle, which would have implications for control recommendations. Three types of S. agalactiae, sequence type (ST) 1, ST23 and ST103 were consistently the most frequent strains among isolates obtained through the national surveillance programme from 2009 to 2011. Herds infected with ST103, which is common in cattle but rarely found in people in Europe, were spatially clustered throughout the study period and across spatial scales. By contrast, strains that are also commonly found in humans, ST1 and ST23, showed no spatial clustering in most or any years of the study, respectively. Introduction of cattle from a positive herd was associated with increased risk of infection by S. agalactiae in the next year (risk ratio of 2.9 and 4.7 for 2009-2010 and 2010-2011, respectively). Moreover, mean exposure to infection was significantly higher for newly infected herds and significantly lower for persistently susceptible herds, as compared to random simulated networks with the same properties, which suggests strong association between the cattle movement network and new infections. At strain-level, new infections with ST1 between 2009 and 2010 were significantly associated with cattle movements, while other strains showed only some degree of association. Sharing of veterinary services, which may serve as proxy for local or regional contacts at a range of scales, was not significantly associated with increased risk of introduction of S. agalactiae or one of the three predominant strains on a farm. Our findings support the reinstatement of restrictions on cattle movements from S. agalactiae positive herds, which came into effect in 2018, but provide insufficient evidence to support strain-specific control recommendations.

Realtime case study simulations of transmission of Pancreas Disease (PD) in Norwegian salmonid farming for disease control purposes

Pancreas Disease (PD) is a viral disease caused by Salmonid Alphavirus (SAV). It affects farmed salmonids in the North Atlantic, and leads to reduced feed intake and increased mortality with reduced production and welfare as a consequence. In 2013, the estimated cost of an outbreak on an average salmon farm was about 6.6 mil €. In Norway, PD has been notifiable since 2008, and regulations to mitigate disease spread are in place. However, despite the regulations, 140-170 farms are affected by PD every year. The aquaculture industry is growing continuously, introducing farms in new geographical areas, and fish are moved between hydrographically separated zones for trade and slaughter. All such movements and relocations need to be approved by the competent authorities. Thus, there is a demand for support to farmers and competent authorities when making decisions on disease management and especially on the effect of moving infected fish. We have used a disease-transmission model for outbreak-simulation in real time for assessing the probability of disease transmission from a farm that gets infected with PD. We have also simulated the effects of three different control-regimes: no stamping-out, delayed stamping-out or immediate stamping-out, on the transmission of PD to surrounding farms. Simulations showed that the immediate stamping out of an infected farm led to effective containment of an outbreak. No stamping out led to up to 32.1% of farms within 100 km of the index farm to become effected. We have used real production data for the model building and the scenario simulations, and the results illustrate that a risk assessment of horizontal disease transmission must be undertaken on a case-by-case basis, because the time and place of the outbreak has a large influence on the risk of transmission.

Healthcare-associated infection impact with bioaerosol treatment and COVID-19 mitigation measures

BACKGROUND

The real-world impact of breathing zone air purification and coronavirus disease 2019 (COVID-19) mitigation measures on healthcare-associated infections is not well documented. Engineering solutions to treat airborne transmission of disease may yield results in controlled test chambers or single rooms, but have not been reported on hospital-wide applications, and the impact of COVID-19 mitigation measures on healthcare-associated infection rates is unknown.

AIM

To determine the impact of hospital-wide bioaerosol treatment and COVID-19 mitigation measures on clinical outcomes.

METHODS

The impact of the step-wise addition of air disinfection technology and COVID-19 mitigation measures to standard multi-modal infection control on particle counts, viral and bacterial bioburden, and healthcare-associated infection rates was investigated in a 124-bed hospital (>100,000 patient-days over 30 months).

FINDINGS AND CONCLUSION

The addition of air disinfection technology and COVID-19 mitigation measures reduced airborne ultrafine particles, altered hospital bioburden, and reduced healthcare-associated infections from 11.9 to 6.6 (per 1000 patient-days) and from 6.6 to 1.0 (per 1000 patient-days), respectively (P<0.0001, R2=0.86). No single technology, tool or procedure will eliminate healthcare-associated infections, but the addition of a ubiquitous facility-wide engineering solution at limited expense and with no alteration to patient, visitor or staff traffic or workflow patterns reduced infections by 45%. A similar impact was documented with the addition of comprehensive, restrictive, and labour- and material-intensive COVID-19 mitigation measures. To the authors' knowledge, this is the first direct comparison between traditional infection control, an engineering solution and COVID-19 mitigation measures.

Gonococcus infection probably acquired from bathing in a natural thermal pool: a case report

BACKGROUND

Authorities need to recognize that, while rare, gonorrhea can be transmitted nonsexually, and should not be presumed definitive evidence of abuse. We report the unusual case of a girl diagnosed with Neisseria gonorrhoeae after bathing in a heavily frequented hot pool at the edge of the crater lake Specchio di Venere ("Mirror of Venus") on Pantelleria Island, Italy.

CASE PRESENTATION

Two days after bathing in the pool, this 11-year-old Austrian girl developed vulvovaginitis that partially settled with antifungal cream. Subsequent swabs cultured positive for Neisseria gonorrhoeae. Family members tested negative. The child adamantly denied any sexual contact, and no opportunities for sexual exposure could be identified. It was therefore concluded that she must have acquired the infection from pool water contaminated by gonococcus after a 2-day incubation period. The infection was successfully treated with ceftriaxone and azithromycin with no adverse effects.

CONCLUSIONS

The pools are shallow, close to body temperature, isotonic, slightly acidic from CO2 bubbles, and contain organic particles, all potentially supporting survival of gonococcus. There are historical case reports in the literature of gonococcal epidemics in children's hospitals being traced to common baths. It is imperative that all cases of gonococcal infection in children are fully investigated, including examining all other relevant family members, to determine whether sexual assault has occurred. This is not a diagnosis to be missed. However, both sexual and nonsexual transmission are possible. A presumption that a gonococcal infection is diagnostic of sexual abuse can be dire, with children wrongfully removed from their parents' care, and their caregivers facing false charges of sexual crimes. Our case serves to illustrate that the very uncommon diagnosis of gonorrhea in a child may be the result of nonsexual transmission of the infection, and that contaminated hot pools are a very rare source of infection that should be considered.

Physical distancing for care delivery in health care settings: Considerations and consequences

As health care systems explore new ways of delivering care for patients with and without COVID-19, they must consider how to maintain physical distancing among health care workers and patients. Physical distancing in high complexity systems such as health care is particularly challenging and may benefit from a human factors and systems engineering perspective. We discuss challenges to implementing and maintaining physical distancing in health care settings and present possible solutions from a human factors and systems engineering perspective.

Multi-agent system collision model to predict the transmission of seasonal influenza in Tokyo from 2014-2015 to 2018-2019 seasons

The objective of this study was to apply the multi-agent system (MAS) collision model to predict seasonal influenza epidemic in Tokyo for 5 seasons (2014-2015 to 2018-2019 seasons). The MAS collision model assumes each individual as a particle inside a square domain. The particles move within the domain and disease transmission occurs in a certain probability when an infected particle collides a susceptible particle. The probability was determined based on the basic reproduction number calculated using the actual data. The simulation started with 1 infected particle and 999 susceptible particles to correspond to the onset of an influenza epidemic. We performed the simulation for 150 days and the calculation was repeated 500 times for each season. To improve the accuracy of the prediction, we selected simulations which have similar incidence number to the actual data in specific weeks. Analysis including all simulations corresponded good to the actual data in 2014-2015 and 2015-2016 seasons. However, the model failed to predict the sharp peak incidence after the New Year Holidays in 2016-2017, 2017-2018, and 2018-2019 seasons. A model which included simulations selected by the week of peak incidence predicted the week and number of peak incidence better than a model including all simulations in all seasons. The reproduction number was also similar to the actual data in this model. In conclusion, the MAS collision model predicted the epidemic curve with good accuracy by selecting the simulations using the actual data without changing the initial parameters such as the basic reproduction number and infection time.

Heterogeneous patterns of COVID-19 transmission in an Urban set up - sero-epidemiological survey data from Ujjain, Madhya Pradesh (a central Indian city)

In the wake of rising number of SARS-CoV-2 cases, the Government of India had placed mass-quarantine measures, termed as "lockdown" measures from end-March 2020. The subsequent phase-wise relaxation from July 2020 led to a surge in the number of cases. This necessitated an understanding of the true burden of SARS-CoV-2 in the community. Consequently, a sero-epidemiological survey was carried out in the central Indian city of Ujjain, Madhya Pradesh. This article details the processes of data acquisition, compilation, handling, and information derivation from the survey. Information on socio-demographic and serological variables were collected from 4,883 participants using a multi-stage stratified random sampling method. Appropriate weightage was calculated for each participant as sampling fraction derived from Primary Sampling Unit (PSU), Secondary Sampling Unit (SSU) and Tertiary Sampling Unit (TSU). The weightage was then applied to the data to adjust the findings at population level. The comprehensive and robust methodology employed here may act as a model for similar future endeavours. At the same time, the dataset can also be relevant for researchers in fields such as data science, epidemiology, virology and earth modelling.

A disproportionate epidemic: COVID-19 cases and deaths among essential workers in Toronto, Canada

Shelter-in-place mandates and closure of nonessential businesses have been central to COVID19 response strategies including in Toronto, Canada. Approximately half of the working population in Canada are employed in occupations that do not allow for remote work suggesting potentially limited impact of some of the strategies proposed to mitigate COVID-19 acquisition and onward transmission risks and associated morbidity and mortality. We compared per-capita rates of COVID-19 cases and deaths from January 23, 2020 to January 24, 2021, across neighborhoods in Toronto by proportion of the population working in essential services. We used person-level data on laboratory-confirmed COVID-19 community cases and deaths, and census data for neighborhood-level attributes. Cumulative per-capita rates of COVID-19 cases and deaths were 3.3-fold and 2.5-fold higher, respectively, in neighborhoods with the highest versus lowest concentration of essential workers. Findings suggest that the population who continued to serve the essential needs of society throughout COVID-19 shouldered a disproportionate burden of transmission and deaths. Taken together, results signal the need for active intervention strategies to complement restrictive measures to optimize both the equity and effectiveness of COVID-19 responses.