Human Disease Outbreaks Research Articles

One Health workers: innovations in early detection of human, animal, and plant disease outbreaks

One Health workers: innovations in early detection of human, animal, and plant disease outbreaks

Ebola spillover correlates with bat diversity

Some of the world’s deadliest diseases and greatest public health challenges are zoonoses from wildlife, such as Ebola (Ebolavirus). Due to the increasing number of cases in recent years, it has been widely hypothesized that increasing human population densities and anthropogenic disturbance largely explain outbreaks of Ebola virus disease in humans. While studies indicate that ebolaviruses are likely hosted by bats (Chiroptera), their role in outbreaks of the disease remains unclear. We tested whether bat species richness (total and within families), human population density, and anthropogenic disturbance explained the occurrence of Ebola virus disease spillovers within Africa using both generalized linear models and Maxent models. We demonstrate that spillover occurred in areas with high species richness of nycterid bats and low levels of both anthropogenic disturbance and human population density. Outbreaks of Ebola virus disease have devastating effects on people and communities and our results provide an important step toward understanding how and where Ebola virus disease may spill over to human populations.

Herpes Simplex Virus: A Versatile Tool for Insights Into Evolution, Gene Delivery, and Tumor Immunotherapy.

Herpesviruses are prevalent throughout the animal kingdom, and they have coexisted and coevolved along with their host species for millions of years. Herpesviruses carry a large (120-230 kb) double-stranded DNA genome surrounded by a protein capsid, a tegument layer consisting of viral and host proteins, and a lipid bilayer envelope with surface glycoproteins. A key characteristic of these viruses is their ability to enter a latent state following primary infection, allowing them to evade the host’s immune system and persist permanently. Herpesviruses can reactivate from their dormant state, usually during times of stress or when the host’s immune responses are impaired. While herpesviruses can cause complications with severe disease in immune-compromised people, most of the population experiences few ill effects from herpesvirus infections. Indeed, herpes simplex virus 1 (HSV-1) in particular has several features that make it an attractive tool for therapeutic gene delivery. Herpes simplex virus 1 targets and infects specific cell types, such as epithelial cells and neurons. The HSV-1 genome can also accommodate large insertions of up to 14 kb. The HSV-1-based vectors have already achieved success for the oncolytic treatment of melanoma. In addition to serving as a vehicle for therapeutic gene delivery and targeted cell lysis, comparative genomics of herpesviruses HSV-1 and 2 has revealed valuable information about the evolutionary history of both viruses and their hosts. This review focuses on the adaptability of HSV-1 as an instrument for gene delivery and an evolutionary marker. Overall, HSV-1 shows great promise as a tool for treating human disease and studying human migration patterns, disease outbreaks, and evolution.

One Health workers: innovations in early detection of human, animal, and plant disease outbreaks

The majority (60%) of human pathogens are zoonotic and 75% of emerging zoonotic pathogens are from wildlife species (eg, Ebola, Zika). In addition, vector, water, and food-borne diseases greatly impact people, livestock, and agriculture and result in adverse effects on local, national, and global economies. Continuous monitoring and surveillance of newly emerging diseases and pandemic outbreaks is a critical component in One Health (OH) which is the term representing the collaboration of multiple disciplines working to achieve optimal health for people, animals, plants/crops, and the environment. For decades a group of minimally trained local workers --community health workers -- (CHWs) have functioned at the interface between community members and whatever health care system existed within a country. Today, around the world CHWs have become the bedrock and frontline health care providers as they deliver or monitor human treatments, engage in the detection of common illness, and offer preventive care. In these same communities there is often severely limited access to veterinary health services which has a negative impact on livestock production with implications for food security, and has led to the inappropriate and indiscriminate use of antibiotics. In rural areas poor field maintenance and common agricultural health problems results in the death or decreased crop production of important food sources. Inappropriate use of pesticides and other products that are toxic to animals and humans often enter the soil or water supply through misuse. This lack of health integration across human, animal, plant, and environmental health sectors in an ever-shrinking world begs for a shift in health services and the creation of a community based One Health Worker.

A key region of molecular specificity orchestrates unique ephrin-B1 utilization by Cedar virus.

The emergent zoonotic henipaviruses, Hendra, and Nipah are responsible for frequent and fatal disease outbreaks in domestic animals and humans. Specificity of henipavirus attachment glycoproteins (G) for highly species-conserved ephrin ligands underpins their broad host range and is associated with systemic and neurological disease pathologies. Here, we demonstrate that Cedar virus (CedV)-a related henipavirus that is ostensibly nonpathogenic-possesses an idiosyncratic entry receptor repertoire that includes the common henipaviral receptor, ephrin-B2, but, distinct from pathogenic henipaviruses, does not include ephrin-B3. Uniquely among known henipaviruses, CedV can use ephrin-B1 for cellular entry. Structural analyses of CedV-G reveal a key region of molecular specificity that directs ephrin-B1 utilization, while preserving a universal mode of ephrin-B2 recognition. The structural and functional insights presented uncover diversity within the known henipavirus receptor repertoire and suggest that only modest structural changes may be required to modulate receptor specificities within this group of lethal human pathogens.

A structural basis for antibody-mediated neutralization of Nipah virus reveals a site of vulnerability at the fusion glycoprotein apex

Nipah virus (NiV) is a highly pathogenic paramyxovirus that causes frequent outbreaks of severe neurologic and respiratory disease in humans with high case fatality rates. The 2 glycoproteins displayed on the surface of the virus, NiV-G and NiV-F, mediate host-cell attachment and membrane fusion, respectively, and are targets of the host antibody response. Here, we provide a molecular basis for neutralization of NiV through antibody-mediated targeting of NiV-F. Structural characterization of a neutralizing antibody (nAb) in complex with trimeric prefusion NiV-F reveals an epitope at the membrane-distal domain III (DIII) of the molecule, a region that undergoes substantial refolding during host-cell entry. The epitope of this monoclonal antibody (mAb66) is primarily protein-specific and we observe that glycosylation at the periphery of the interface likely does not inhibit mAb66 binding to NiV-F. Further characterization reveals that a Hendra virus-F-specific nAb (mAb36) and many antibodies in an antihenipavirus-F polyclonal antibody mixture (pAb835) also target this region of the molecule. Integrated with previously reported paramyxovirus F-nAb structures, these data support a model whereby the membrane-distal region of the F protein is targeted by the antibody-mediated immune response across henipaviruses. Notably, our domain-specific sequence analysis reveals no evidence of selective pressure at this region of the molecule, suggestive that functional constraints prevent immune-driven sequence variation. Combined, our data reveal the membrane-distal region of NiV-F as a site of vulnerability on the NiV surface.

Emerging infectious disease, the household built environment characteristics, and urban planning: Evidence on avian influenza in Vietnam

Recent concerns with pandemic outbreaks of human disease and their origins in animal populations have ignited concerns regarding connections between Emerging Infectious Diseases (EID) and development. As disasters, health, and infectious disease become part of planning concern (Matthew & McDonald, 2007), greater focus on household infrastructure and EID disease outbreaks among poultry is warranted. Following Spencer (2013), this study examines the relationship between the mix of household-scale water supplies, sanitation systems, and construction materials, and Highly Pathogenic Avian Influenza (HPAI) among poultry in a developing country: Vietnam. Findings of our multivariate logistic regressions suggest that a non-linear, Kuznets-shaped urban transition (Spencer, 2013) has an independent effect on the outbreak of HPAI, especially as it relates to household-level sanitation infrastructure. We conclude that the Kuznets-shape development of household infrastructure characteristics in Vietnam play a significant role in explaining where poultry outbreaks occur. Using secondary data from the Census of Population and Housing, and the Agricultural Census at the District and Commune levels for the country of Vietnam, we performed logistic regression to test the relationship between outbreaks of HPAI in poultry and newly-developed “coherence indices” (Spencer, 2013) of household water supply, sanitation, and construction materials that measure nonlinear, transitional development. Results show that district-scale coherence indices are negatively and independently correlated with HPAI outbreaks, especially for sanitation. Findings also suggest that community-scale coherence of urban infrastructures is a powerful tool for predicting where HPAI poultry outbreaks are likely to occur, thereby providing health planners new tools for efficient surveillance.

Epidemiological Aspects of Escherichia albertii Outbreaks in Japan and Genetic Characteristics of the Causative Pathogen.

Zoonotic pathogen Escherichia albertii has been identified as the cause of several human disease outbreaks; however, factors such as the general symptoms and incubation period of E. albertii infection have yet to be defined. Therefore, we aimed to determine the unique aspects of E. albertii outbreaks in Japan and to examine the genetic characteristics of the causative pathogen. We studied all known E. albertii outbreaks that occurred in Japan up until 2015, which consisted of five confirmed outbreaks and one putative outbreak (Outbreaks 1-6). Outbreaks were re-examined based on personal communications between researchers in prefectural and municipal public health institutes, and through examination of any published study conducted at the time. Draft genome sequences of outbreak-associated E. albertii isolates were also generated. The most common symptom displayed by patients across the six episodes was watery diarrhea (>80%), followed by abdominal pain (50-84%) and fever (37.0-39.5°C) (26-44%). The estimated average incubation period of E. albertii infection was 12-24 h. We assumed that most of the outbreaks were foodborne or waterborne, with restaurant foods, restaurant water, and boxed lunches being the suspected transmission vehicles. Three of the six outbreak-associated E. albertii isolates possessed intact ETT2 regions, while the remaining isolates contained disrupted ETT2-encoding genes. Virulence gene screening revealed that more than half (44/70) of the tested genes were present in all 5 strains examined, and that each of the strains contained more than 1 gene from 14 out of the 21 groups of virulence genes examined in this study. The five E. albertii strains were classified into four of the five known phylogroups. Therefore, we determined that multiple E. albertii genotypes in Japan have the potential to cause outbreaks of diarrhea, abdominal pain, and/or fever following infection of a human host.

Rotavirus Species B Encodes a Functional Fusion-Associated Small Transmembrane Protein.

Rotavirus is an important cause of diarrheal disease in young mammals. Rotavirus species A (RVA) causes most human rotavirus diarrheal disease and primarily affects infants and young children. Rotavirus species B (RVB) has been associated with sporadic outbreaks of human adult diarrheal disease. RVA and RVB are predicted to encode mostly homologous proteins but differ significantly in the proteins encoded by the NSP1 gene. In the case of RVB, the NSP1 gene encodes two putative protein products of unknown function, NSP1-1 and NSP1-2. We demonstrate that human RVB NSP1-1 mediates syncytium formation in cultured human cells. Based on sequence alignment, NSP1-1 proteins from species B, G, and I contain features consistent with fusion-associated small transmembrane (FAST) proteins, which have previously been identified in other genera of the Reoviridae family. Like some other FAST proteins, RVB NSP1-1 is predicted to have an N-terminal myristoyl modification. Addition of an N-terminal FLAG peptide disrupts NSP1-1-mediated fusion. NSP1-1 from a human RVB mediates fusion of human cells but not hamster cells and, thus, may serve as a species tropism determinant. NSP1-1 also can enhance RVA replication in human cells, both in single-cycle infection studies and during a multicycle time course in the presence of fetal bovine serum, which inhibits rotavirus spread. These findings suggest potential yet untested roles for NSP1-1 in RVB species tropism, immune evasion, and pathogenesis.IMPORTANCE While species A rotavirus is commonly associated with diarrheal disease in young children, species B rotavirus has caused sporadic outbreaks of adult diarrheal disease. A major genetic difference between species A and B rotaviruses is the NSP1 gene, which encodes two proteins for species B rotavirus. We demonstrate that the smaller of these proteins, NSP1-1, can mediate fusion of cultured human cells. Comparison with viral proteins of similar function provides insight into NSP1-1 domain organization and fusion mechanism. These comparisons suggest that there is a fatty acid modification at the amino terminus of the protein, and our results show that an intact amino terminus is required for NSP1-1-mediated fusion. NSP1-1 from a human virus mediates fusion of human cells, but not hamster cells, and enhances species A rotavirus replication in culture. These findings suggest potential, but currently untested, roles for NSP1-1 in RVB host species tropism, immune evasion, and pathogenesis.

Polioencephalomyelitis in Domestic Swine Associated With Porcine Astrovirus Type 3.

In the past decade, different members of the genus Mamastrovirus have been associated with outbreaks of neurologic disease in humans, cattle, sheep, mink, and, most recently, porcine astrovirus 3 (PoAstV3) in swine. We performed a retrospective analysis of 50 cases of porcine neurologic disease of undetermined cause but with microscopic lesions compatible with a viral encephalomyelitis to better understand the role and pathogenesis of PoAstV3 infection. Nucleic acid was extracted from formalin-fixed paraffin-embedded (FFPE) tissue for reverse transcription quantitative polymerase chain reaction (RT-qPCR) testing for PoAstV3. In addition, 3 cases with confirmed PoAstV3-associated disease were assayed by RT-qPCR to investigate PoAstV3 tissue distribution. PoAstV3 was detected in central nervous system (CNS) tissue via RT-qPCR and in situ hybridization in 13 of 50 (26%) FFPE cases assayed. PoAstV3 was rarely detected in any tissues outside the CNS. Positive cases from the retrospective study included pigs in various production categories beginning in 2010, the earliest year samples were available. Based on these results, PoAstV3 appears to be a recurring putative cause of viral encephalomyelitis in swine that is rarely detected outside of the CNS at the time of clinical neurologic disease, unlike other common viral causes of neurologic disease in swine.

On the Fly: Interactions Between Birds, Mosquitoes, and Environment That Have Molded West Nile Virus Genomic Structure Over Two Decades.

West Nile virus (WNV) was first identified in North America almost 20 yr ago. In that time, WNV has crossed the continent and established enzootic transmission cycles, resulting in intermittent outbreaks of human disease that have largely been linked with climatic variables and waning avian seroprevalence. During the transcontinental dissemination of WNV, the original genotype has been displaced by two principal extant genotypes which contain an envelope mutation that has been associated with enhanced vector competence by Culex pipiens L. (Diptera: Culicidae) and Culex tarsalis Coquillett vectors. Analyses of retrospective avian host competence data generated using the founding NY99 genotype strain have demonstrated a steady reduction in viremias of house sparrows over time. Reciprocally, the current genotype strains WN02 and SW03 have demonstrated an inverse correlation between house sparrow viremia magnitude and the time since isolation. These data collectively indicate that WNV has evolved for increased avian viremia while house sparrows have evolved resistance to the virus such that the relative host competence has remained constant. Intrahost analyses of WNV evolution demonstrate that selection pressures are avian species-specific and purifying selection is greater in individual birds compared with individual mosquitoes, suggesting that the avian adaptive and/or innate immune response may impose a selection pressure on WNV. Phylogenomic, experimental evolutionary systems, and models that link viral evolution with climate, host, and vector competence studies will be needed to identify the relative effect of different selective and stochastic mechanisms on viral phenotypes and the capacity of newly evolved WNV genotypes for transmission in continuously changing landscapes.

Plant variety and soil type influence Escherichia coli O104:H4 strain C227/11ϕcu adherence to and internalization into the roots of lettuce plants

Human disease outbreaks caused by pathogenic Escherichia coli are increasingly associated with the consumption of contaminated fresh produce. Internalization of enteroaggregative/enterohemorrhagic E. coli (EAEC/EHEC) strains into plant tissues may present a serious threat to public health. In the current study, the ability of the fluorescing Shiga toxin-negative E. coli O104:H4 strain C227/11ϕcu/pKEC2 to adhere to and to internalize into the roots of Lactuca sativa and Valerianella locusta grown in diluvial sand (DS) and alluvial loam (AL) was investigated. In parallel, the soil microbiota was analyzed by partial 16S rRNA gene sequencing. The experiments were performed in a safety level 3 greenhouse to simulate agricultural practice. The adherence of C227/11ϕcu/pKEC2 to the roots of both plant varieties was increased by at least a factor three after incubation in DS compared to AL. Compared to V. locusta, internalization into the roots of L. sativa was increased 12-fold in DS and 108-fold in AL. This demonstrates that the plant variety had an impact on the internalization ability, whereas for a given plant variety the soil type also affected bacterial internalization. In addition, microbiota analysis detected the inoculated strain and showed large differences in the bacterial composition between the soil types.

Salmonella recovery from chicken bone marrow and cecal counts differ by pathogen challenge method.

Mechanically separated chicken (MSC) may be incorporated into other further processed foods, and has been identified as a transmission vehicle in human foodborne disease outbreaks involving the pathogen Salmonella enterica. Chickens possess pneumatic bones producing marrow, which may become infected with Salmonella and present a mechanism for Salmonella contamination of MSC. The primary objective of the current study was to ascertain whether chicken bone marrow was susceptible to Salmonella infection as a function of pathogen challenge method. Additionally, this study sought to determine the impact of Salmonella challenge site and inoculation on subsequent numbers of the microorganism in the cecum at 3, 6 and 9 d post-challenge. In this study, 30-day-old birds (Gallus domesticus) were separately challenged with S. enterica by one of the 6 experimental treatment methods: oral or endo-tracheal gavage, and transdermal scratch challenge on the breast or back muscles, with or without feathers (N = 150). Differing Salmonella recovery rates were detected in bone marrow from euthanized birds (P = 0.0015); oral and endo-tracheal gavage produced Salmonella recovery frequencies of 10% and 20%, respectively. Counts of Salmonella from chicken cecal samples statistically differed as a function of challenge method (P = 0.032); the highest numbers of Salmonella in cecal samples were obtained from orally gavaged birds (3.0 log10 cfu/g). Study results demonstrate the potential for chickens to contract short-term systemic infection following Salmonella challenge using methods of pathogen challenge simulating aerosol inhalation, ingestion, or wounding. Salmonella entry into chicken bone marrow may result in decreased likelihood of Salmonella performance standard compliance and increased pathogen transmission risk to consumers.

Non-biogroup 1 or 2 Strains of the Emerging Zoonotic Pathogen Escherichia albertii, Their Proposed Assignment to Biogroup 3, and Their Commonly Detected Characteristics.

Escherichia albertii, a zoonotic enteropathogen, is responsible for outbreaks of disease in humans. Identifying strains of E. albertii by phenotypic characterization tests is difficult because of its poorly defined properties. Screening its phenotypic characteristics is, nevertheless, a necessary prerequisite for further genetic analysis of its properties, and species-specific polymerase chain reaction (PCR) analysis can be used to type the pathogen. While two E. albertii biogroups (1 and 2) have been described, strains with characteristics divergent from both biogroups have been reported worldwide. The aim of the present study was to evaluate the characteristics of non-biogroup 1 or 2 strains, and discern the characteristics common to all of the E. albertii strains from this study. Altogether, 107/414 field isolates were selected for examination based on pulsed-field gel electrophoresis analysis. The 107 strains were isolated from 92 sources, including humans and pigeon feces, other wild birds, and retail chicken livers. All strains were then examined using various culture-based, biochemical (API 50CHE tests, API Zym test, and others) and molecular (virulence gene screening, multi-locus sequence analysis) testing methods. Our results revealed that all field strains (n = 107) showed non-biogroup 1 or 2 characteristics, with multiple sequence differences. Variations in indole production and the lysine decarboxylase activity profiles among the isolates made identification of E. albertii very difficult. Therefore, we propose that non-biogroup 1 or 2 of E. albertii should be assigned to biogroup 3 to make screening of them easier in public health and clinical laboratory settings. Clearly, having group criteria for indole-negative/lysine-positive, indole-positive/lysine-negative, and indole-positive/lysine-positive E. albertii biogroups 1, 2, and 3 strains, respectively, should provide for more accurate identification of E. albertii isolates. Based on our findings, we recommend that isolates displaying phenotype mobility-negativity (sulfide-indole-motility medium, 37°C), hydrogen sulfide production-negativity (triple sugar iron medium), acid production-negativity from xylose, negative β-glucuronidase activity properties, and showing indole production and lysine decarboxylase activity profiles in accordance with one of the three biogroups, should be further assessed using an E. albertii-specific PCR assay.

Data capture and visualization for a canine influenza outbreak — New York City, 2018

ObjectiveThe objectives of this project were to rapidly build and deploy a web-based reporting platform in response to a canine influenza H3N2 outbreak in New York City (NYC) and provide aggregate data back to the veterinary community as an interactive dashboard.IntroductionData-driven decision-making is a cornerstone of public health emergency response; therefore, a highly-configurable and rapidly deployable data capture system with built-in quality assurance (QA; e.g., completeness, standardization) is critical.1 Additionally, to keep key stakeholders informed of developments during an emergency, data need to be shared in a timely and effective manner. Dynamic data visualization is a particularly useful means of sharing data with healthcare providers and the public.2During Spring 2018, detection of canine influenza H3N2 among dogs in NYC caused concern in the veterinary community. Canine influenza is a highly contagious respiratory infection caused by an influenza A virus.3 However, no central database existed in NYC to monitor the outbreak and no single agency was responsible for data capture. Our team at the NYC Department of Health and Mental Hygiene (DOHMH) partnered with the NYC Veterinary Medical Association (VMA) to monitor the canine influenza H3N2 outbreak by building a web-based reporting platform and interactive dashboard.MethodsThe NYC DOHMH built and deployed a web-based reporting platform to aid veterinarians in reporting cases of canine influenza. We leveraged REDCap Cloud, a cloud-based graphical user interface data capture and management software. REDCap Cloud collected information regarding the provider, owner, dog, residence of dog, illness history, and influenza testing. We leveraged REDCap QA functionality in the form of mandatory questions to ensure data completeness. Several different field types — including dropdown menus, mutually exclusive radio buttons, and multi-select check boxes — were used to ensure data standardization. Skip logic was incorporated to guide users through unique sequences of questions based on the answers they entered. Reporting was voluntary.ResultsAfter requirements were gathered, the REDCap web-based reporting platform was rapidly deployed in approximately two business days. Over the course of one week, multiple versions of the dashboard were produced and the final iteration was completed. The entire system was built on server-side software that is available as free or open-source for individual licenses. The dashboard can be found at the following link: http://www.vmanyc.org/canine_influenza_dashboard.html.A total of 28 cases were reported by 6 providers during June–August 2018. All of the 28 cases were reported from 2 of the 5 NYC counties (boroughs); 17/28 (60.7%) were reported from Brooklyn and 11/28 (39.3%) were reported from Manhattan. We were able to collect mostly complete data by leveraging REDCap QA functionality. The reporting facility was listed in all cases, and an owner was listed in all but two cases. All reported cases used a PCR test for the detection of canine influenza H3N2. One reported case indicated polymerase chain reaction (PCR) test results as “not detected” which suggests that one negative case was reported through the system.ConclusionsUsing REDCap Cloud and R, we were able to rapidly build and deploy a web-based reporting platform and dynamic data visualization during an emergency response to an outbreak of canine influenza H3N2. Our system was used by veterinarians to report 28 cases of canine influenza. Future emergency responses for human disease outbreaks will likely benefit from the experience our team gained during our partnership with the NYC VMA.

Perfect counterfactuals for epidemic simulations.

Simulation studies are often used to predict the expected impact of control measures in infectious disease outbreaks. Typically, two independent sets of simulations are conducted, one with the intervention, and one without, and epidemic sizes (or some related metric) are compared to estimate the effect of the intervention. Since it is possible that controlled epidemics are larger than uncontrolled ones if there is substantial stochastic variation between epidemics, uncertainty intervals from this approach can include a negative effect even for an effective intervention. To more precisely estimate the number of cases an intervention will prevent within a single epidemic, here we develop a 'single-world' approach to matching simulations of controlled epidemics to their exact uncontrolled counterfactual. Our method borrows concepts from percolation approaches, prunes out possible epidemic histories and creates potential epidemic graphs (i.e. a mathematical representation of all consistent epidemics) that can be 'realized' to create perfectly matched controlled and uncontrolled epidemics. We present an implementation of this method for a common class of compartmental models (e.g. SIR models), and its application in a simple SIR model. Results illustrate how, at the cost of some computation time, this method substantially narrows confidence intervals and avoids nonsensical inferences. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.

Applying optimal control theory to complex epidemiological models to inform real-world disease management.

Mathematical models provide a rational basis to inform how, where and when to control disease. Assuming an accurate spatially explicit simulation model can be fitted to spread data, it is straightforward to use it to test the performance of a range of management strategies. However, the typical complexity of simulation models and the vast set of possible controls mean that only a small subset of all possible strategies can ever be tested. An alternative approach-optimal control theory-allows the best control to be identified unambiguously. However, the complexity of the underpinning mathematics means that disease models used to identify this optimum must be very simple. We highlight two frameworks for bridging the gap between detailed epidemic simulations and optimal control theory: open-loop and model predictive control. Both these frameworks approximate a simulation model with a simpler model more amenable to mathematical analysis. Using an illustrative example model, we show the benefits of using feedback control, in which the approximation and control are updated as the epidemic progresses. Our work illustrates a new methodology to allow the insights of optimal control theory to inform practical disease management strategies, with the potential for application to diseases of humans, animals and plants. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.

A probabilistic census-travel model to predict introduction sites of exotic plant, animal and human pathogens.

International travel offers an extensive network for new and recurring human-mediated introductions of exotic infectious pathogens and biota, freeing geographical constraints. We present a predictive census-travel model that integrates international travel with endpoint census data and epidemiological characteristics to predict points of introduction. Population demographics, inbound and outbound travel patterns, and quantification of source strength by country are combined to estimate and rank risk of introduction at user-scalable land parcel areas (e.g. state, county, zip code, census tract, gridded landscapes (1 mi2, 5 km2, etc.)). This risk ranking by parcel can be used to develop pathogen surveillance programmes, and has been incorporated in multiple US state/federal surveillance protocols. The census-travel model is versatile and independent of pathosystems, and applies a risk algorithm to generate risk maps for plant, human and animal contagions at different spatial scales. An interactive, user-friendly interface is available online (https://epi-models.shinyapps.io/Census_Travel/) to provide ease-of-use for regulatory agencies for early detection of high-risk exotics. The interface allows users to parametrize and run the model without knowledge of background code and underpinning data.This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’. This theme issue is linked with the earlier issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’.

New methodologies for the estimation of population vulnerability to diseases: a case study of Lassa fever and Ebola in Nigeria and Sierra Leone.

Public health practitioners require measures to evaluate how vulnerable populations are to diseases, especially for zoonoses (i.e. diseases transmitted from animals to humans) given their pandemic potential. These measures would be valuable to support strategic and operational decision making and allocation of resources. Although vulnerability is well defined for natural hazards, for public health threats the concept remains undetermined. Here, we develop new methodologies to: (i) quantify the impact of zoonotic diseases and the capacity of countries to cope with these diseases, and (ii) combine these two measures (impact and capacity) into one overall vulnerability indicator. The adaptive capacity is calculated from estimations of disease mortality, although the method can be adapted for diseases with no or low mortality but high morbidity. As an example, we focused on the vulnerability of Nigeria and Sierra Leone to Lassa Fever and Ebola. We develop a simple analytical form that can be used to estimate vulnerability scores for different spatial units of interest, e.g. countries or regions. We show how some populations can be highly vulnerable despite low impact threats. We finally outline future research to more comprehensively inform vulnerability with the incorporation of relevant factors depicting local heterogeneities (e.g. bio-physical and socio-economic factors). This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.

How decision makers can use quantitative approaches to guide outbreak responses.

Decision makers are responsible for directing staffing, logistics, selecting public health interventions, communicating to professionals and the public, planning future response needs, and establishing strategic and tactical priorities along with their funding requirements. Decision makers need to rapidly synthesize data from different experts across multiple disciplines, bridge data gaps and translate epidemiological analysis into an operational set of decisions for disease control. Analytic approaches can be defined for specific response phases: investigation, scale-up and control. These approaches include: improved applications of quantitative methods to generate insightful epidemiological descriptions of outbreaks; robust investigations of causal agents and risk factors; tools to assess response needs; identifying and monitoring optimal interventions or combinations of interventions; and forecasting for response planning. Data science and quantitative approaches can improve decision-making in outbreak response. To realize these benefits, we need to develop a structured approach that will improve the quality and timeliness of data collected during outbreaks, establish analytic teams within the response structure and define a research agenda for data analytics in outbreak response.This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’. This theme issue is linked with the earlier issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’.