Disease Control Purposes Research Articles

Epidemic dynamics of cholera with impulsive sanitation

In this work, we develop an ordinary differential equation (ODE) model with impulsive sanitation of cholera. The sanitation interventions are classified into three types in this article. The first two types are human sanitation, with type-1 sanitation focused on the prevention of direct and indirect transmissions and type-2 focused on prevention of bacterial shedding. The third type refers to pathogen sanitation where interventions are performed in contaminated water environment via disinfection. For the developed impulsive model, we introduce the basic production number R0 and show that R0 remains a sharp disease threshold parameter despite the incorporation of impulsive sanitation. We numerically investigate the impact of impulsive sanitation on the prevention and control of the disease. Our numerical results indicate that type-1 sanitation tends to bear the longest time window between subsequent interventions among all the three types of sanitation provided the same level of sanitation efficacy. Particularly, when the sanitation efficacy is 50% under 90% compliance, type-1 sanitation can be implemented about every 7 months for the purpose of disease control, whereas type-2 and type-3 sanitation will have be performed on a daily basis and every three weeks or so, respectively.

Flow Modeling of a Non-Newtonian Viscous Fluid in Elastic-Wall Microchannels

The use of polymer microspheres is becoming increasingly widespread. Along with their most common applications, they are beginning to be used in the synthesis of photonic crystals, microstructure analysis and multiplexed diagnostics for disease control purposes. This paper presents a simple mathematical model that allows us to study the transport mechanisms involved in the deformation of an elastic microchannel under the flow stream of a power-law fluid. In particular, we analyze the momentum transfer to a non-Newtonian fluid (Polydimethylsiloxane, PDMS) due to the deformation of the elastic ceiling of a rectangular microchannel. Hooke’s law is used to represent the stress–deformation relationship of the PDMS channel ceiling. Stop-flow lithography is modeled, and the pressure exerted by the deformed PDMS ceiling on the fluid when the microchannel returns to its original form is taken into account. It is found that the response time of the elastic ceiling deformation increases with the channel width and length and decreases with the channel height independently of the power-law exponent of the injected fluid. However, an increase in the power-law exponent beyond unity causes an increase in the wall-deformation response time and the maximum deformation of the channel height compared to a Newtonian fluid.

Estimating the true number of people with acute rheumatic fever and rheumatic heart disease from two data sources using capture-recapture methodology.

ObjectiveIn Australia, accurate case ascertainment of acute rheumatic fever (ARF) and rheumatic heart disease (RHD) diagnoses for disease surveillance and control purposes requires the use of multiple data sources, including RHD registers and hospitalisation records. Despite drawing on multiple data sources, the true burden of ARF/RHD is likely to be underestimated.MethodsThis study used capture-recapture methods to quantify the missing number of ARF/RHD cases in data from hospitals and jurisdictional RHD registers. Linked datasets comprised reported cases of ARF/RHD in register records and administrative hospital data.ResultsCapture-recapture analyses indicated the total number of new ARF/RHD cases in three Australian jurisdictions (Queensland, South Australia and Western Australia), among people aged 3-54years, was 3480 (95% CI=3366-3600) during 2011-2016. This included 894 (25.7%) individuals who were not listed in either the hospital or register datasets. Non-Indigenous, urban and older people with ARF/RHD were least likely to be identified in either the hospital or register data sources.ConclusionsThe 894 likely ARF/RHD cases our analyses detected that are not included in the routine surveillance datasets are concerning and quantify the magnitude and characteristics of under-notification to RHD registers in Australia, especially for groups that are not typically at high risk of ARF.

Detection and Identification Methods and Control Techniques for Crop Seed Diseases

Seeds comprise an important way in which plant pathogens are introduced into new areas, and serve as carriers for their survival from one planting season to another. Seed health is a recognized factor in modern agricultural science, and affects ideal plant populations and good harvests. Seed disease is one of the most important biological constraints in seed production worldwide. Effective and rapid detection and identification methods for seed disease comprise an important step in crop management, and a measure to protect seeds from pathogens. The detection of seed diseases is usually divided into three categories: traditional detection, immunological detection, and bioinformatics-based detection. The detection methods used for different types of pathogens also vary. For the prevention and control of seed diseases, appropriate methods should also be adopted, such as physical methods, chemical methods, and biological methods. They can be used alone or in combination to achieve the purpose of disease prevention and control. Therefore, this article reviews some important crop seed diseases, their detection and identification methods, and control techniques, in order to provide a theoretical basis for the comprehensive prevention and effective control of seed diseases.

Multi-objective optimization of cordon sanitaire considering operation cost and queueing equity

ABSTRACT This paper aims topropose a method to determine the optimal deployment of cordon sanitaire for epidemic control. A bi-level multi-objective programming model is proposed where the lower level is transportation system equilibrium with queueing time to predict link traffic flow, and the upper level is queueing network design, which is a multi-objective integer nonlinear programming model. The primary objective is to minimize the total operation cost of servers with a predetermined waiting time constraint, and the secondary objective is to reach queueing equity. A heuristic algorithm is designed where the method of successive averages is adopted for the lower-level model, and a genetic algorithm is designed for the upper-level model. The computational results show that the methods can find a good heuristic optimal solution. These methods are useful for planners to determine the optimal deployment of cordon sanitaire for disease control and prevention purposes.

Genome-wide association studies for the identification of cattle susceptible and resilient to paratuberculosis.

Mycobacterium avium subsp. paratuberculosis (MAP) causes Johne's disease or paratuberculosis (PTB), with important animal health and economic implications. There are no therapeutic strategies to control this disease, and vaccination with inactivated vaccines is limited in many countries because it can interfere with the intradermal test used for bovine tuberculosis detection. Thus, infected animals either get culled after a positive ELISA or fecal PCR result or die due to clinical disease. In this study, we review recent studies aimed to discover genetic markers which could help to identify and select cattle less susceptible and more resilient to PTB. In recent years, the genotyping and subsequent imputation to whole-genome sequence (WGS) has allowed the identification of single-nucleotide polymorphisms (SNPs), quantitative trait loci (QTL), and candidate genes in the Bos taurus genome associated with susceptibility to MAP infection. In most of these genome-wide association studies (GWAS), phenotypes were based on ante-mortem test results including serum ELISA, milk ELISA, and detection of MAP by fecal PCR and bacteriological culture. Cattle infected with MAP display lesions with distinct severity but the associations between host genetics and PTB-associated pathology had not been explored until very recently. On the contrary, the understanding of the mechanisms and genetic loci influencing pathogen resistance, and disease tolerance in asymptomatic individuals is currently very limited. The identification of long-time asymptomatic cattle that is able to resist the infection and/or tolerate the disease without having their health and milk production compromised is important for disease control and breeding purposes.

Decoding China's COVID-19 Health Code Apps: The Legal Challenges.

Heath code apps, along with robust testing, isolation, and the care of cases, are a vital strategy for containing the spread of the COVID-19 outbreak in China. They have remained stable and consistent, allowing China to extensively restore its social and economic development. However, the ethical and legal boundaries of deploying health code apps for disease surveillance and control purposes are unclear, and a rapidly evolving debate has emerged around the promises and risks of their fast promotion. The article outlines the legal challenges by applying the core values of the Personal Information Protection Law (PIPL), the fundamental law for personal information protection in China, into the context of the nationwide use of health code apps. It elaborates on the balance between the demands for upholding individuals’ rights to the security of their personal information and those for public access to such information to prevent the spread of infectious diseases. It identifies the current gaps in addressing personal information harms during the use of the apps, particularly with regard to user consent, transparency, necessity, storage duration, and security safeguards.

Forecasting Scrub Typhus Cases in Eight High-Risk Counties in China: Evaluation of Time-Series Model Performance

Scrub typhus (ST) is expanding its geographical distribution in China and in many regions worldwide raising significant public health concerns. Accurate ST time-series modeling including uncovering the role of environmental determinants is of great importance to guide disease control purposes. This study evaluated the performance of three competing time-series modeling approaches at forecasting ST cases during 2012–2020 in eight high-risk counties in China. We evaluated the performance of a seasonal autoregressive-integrated moving average (SARIMA) model, a SARIMA model with exogenous variables (SARIMAX), and the long–short term memory (LSTM) model to depict temporal variations in ST cases. In our investigation, we considered eight environmental variables known to be associated with ST landscape epidemiology, including the normalized difference vegetation index (NDVI), temperature, precipitation, atmospheric pressure, sunshine duration, relative humidity, wind speed, and multivariate El Niño/Southern Oscillation index (MEI). The first 8-year data and the last year data were used to fit the models and forecast ST cases, respectively. Our results showed that the inclusion of exogenous variables in the SARIMAX model generally outperformed the SARIMA model. Our results also indicate that the role of exogenous variables with various temporal lags varies between counties, suggesting that ST cases are temporally non-stationary. In conclusion, our study demonstrates that the approach to forecast ST cases needed to take into consideration local conditions in that time-series model performance differed between high-risk areas under investigation. Furthermore, the introduction of time-series models, especially LSTM, has enriched the ability of local public health authorities in ST high-risk areas to anticipate and respond to ST outbreaks, such as setting up an early warning system and forecasting ST precisely.

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.

A comprehensive investigation of the microbial risk of secondary water supply systems in residential neighborhoods in a large city

Secondary water supply systems (SWSSs) are characterized by long water stagnation and low levels of chlorine residuals, which may pose a high microbial risk to terminal users. In this study, the SWSSs of 12 residential neighborhoods in a metropolitan area of 5 million people in southeastern China were seasonally investigated to assess their microbial risks by determining more than 30 physicochemical and biological parameters. Although the microbiological quality of SWSS water met the requirements of the standards for drinking water quality of China, it did deteriorate in various aspects. The heterotrophic plate counts with R2A media were high (> 100 CFU/mL) in some SWSS tank and tap water samples. Propidium monoazide (PMA)-qPCR revealed a one magnitude higher abundance of viable bacteria in the tank and tap water samples (average 103.63±1.10 and 103.65±1.25 gene copies/mL, respectively) compared with the input water samples, and Enterococcus, Acanthamoeba, and Hartmannella vermiformis were only detected in the tanks. In particular, the high detection frequency of Legionella in 35% tank and 21% tap water samples suggested it is a supplementary microbial safety indicator in SWSSs. The microbial regrowth potential was more obvious in summer, and Illumina sequencing also demonstrated distinct seasonal changes in the relative abundance of bacterial gene sequences at the genus level. Turbidity and residual chlorine were closely connected with total bacterial biomass, and the latter seemed responsible for microbial community structure alteration. The extremely low chlorine residuals associated with a high abundance of total bacteria (as high as 106.48 gene copies/mL) and Legionella (as high as 106.71 gene copies/100 mL) in the closed valve tanks highlighted the high microbial risk increased by mishandling the operation of SWSSs. This study found that SWSSs possessed a higher microbial risk than the drinking water network, which suggested that the frequency and scope of monitoring the microbial risk of SWSSs in megacities should be strengthened for the purpose of waterborne epidemic disease prevention and control.

Covid-19 antigen testing: better than we know? A test accuracy study

Background Antigen testing for SARS-CoV-2 is considered to be less sensitive than the standard reference method – real-time PCR (RT-PCR). It has been suggested that many patients with positive RT-PCR ‘missed’ by antigen testing might be non-infectious. Methods In a real-world high-throughput setting for asymptomatic or mildly symptomatic patients, 494 patients were tested using RT-PCR as well as a single lateral flow antigen test (Ecotest, AssureTech, China). Where the results differed, virus viability was evaluated by cell culture. The test parameters were calculated with RT-PCR and RT-PCR adjusted on viability as reference standards. Results The overall sensitivity of the used antigen test related to the RT-PCR only was 76.2%, specificity was 97.3%. However, 36 out of 39 patients ‘missed’ by the antigen test contained no viable virus. After adjusting on that, the sensitivity grew to 97.7% and, more importantly for disease control purposes, the negative predictive value reached 99.2%. Conclusions We propose that viability testing should be always performed when evaluating a new antigen test. A well-chosen and validated antigen test provides excellent results in identifying patients who are shedding viable virus (although some caveats still remain) in the real-world high-throughput setting of asymptomatic or mildly symptomatic individuals.

Key Learnings During the Development of a Generic Data Collection Tool to Support Assessment of Freedom of Infection in Cattle Herds.

Various European Member States have implemented control or eradication programmes for endemic infectious diseases in cattle. The design of these programmes varies between countries and therefore comparison of the outputs of different control programmes is complex. Although output-based methods to estimate the confidence of freedom resulting from these programmes are under development, as yet there is no practical modeling framework applicable to a variety of infectious diseases. Therefore, a data collection tool was developed to evaluate data availability and quality and to collect actual input data required for such a modeling framework. The aim of the current paper is to present the key learnings from the process of the development of this data collection tool. The data collection tool was developed by experts from two international projects: STOC free (Surveillance Tool for Outcome-based Comparison of FREEdom from infection, www.stocfree.eu) and SOUND control (Standardizing OUtput-based surveillance to control Non-regulated Diseases of cattle in the EU, www.sound-control.eu). Initially a data collection tool was developed for assessment of freedom of bovine viral diarrhea virus in six Western European countries. This tool was then further generalized to enable inclusion of data for other cattle diseases i.e., infectious bovine rhinotracheitis and Johne's disease. Subsequently, the tool was pilot-tested by a Western and Eastern European country, discussed with animal health experts from 32 different European countries and further developed for use throughout Europe. The developed online data collection tool includes a wide range of variables that could reasonably influence confidence of freedom, including those relating to cattle demographics, risk factors for introduction and characteristics of disease control programmes. Our results highlight the fact that data requirements for different cattle diseases can be generalized and easily included in a data collection tool. However, there are large differences in data availability and comparability across European countries, presenting challenges to the development of a standardized data collection tool and modeling framework. These key learnings are important for development of any generic data collection tool for animal disease control purposes. Further, the results can facilitate development of output-based modeling frameworks that aim to calculate confidence of freedom from disease.

COVID-19 Antigen Testing: Better than We Know?

Background: Antigen testing (AGT) for SARS-CoV-2 is generally considered to be less sensitive than the standard reference method – RT-PCR. It has been suggested that a significant part of patients with positive RT-PCR “missed” by AGT might be free of viable virus and, thus, non-infectious. However, to the best of our knowledge, no head-to-head comparison of this has been performed so far.Methods: In a screening setting for asymptomatic or mildly symptomatic patients, 496 patients were tested using RT-PCR as well as a single AGT. Where the results differed, virus viability was evaluated by culture on CV-1 cells. Screening test parameters were calculated with RT-PCR and RT-PCR corrected on viability as reference standards.Findings: The sensitivity of the used AGT related to the RT-PCR only was mere 76·2%. However, 36 out of 39 patients “missed” by AGT contained no viable virus. After correction on that, the sensitivity grew to 97·7% and, more importantly for disease control purposes, the negative predictive value reached 99·2%.Interpretation: We propose that viability testing should be always performed when evaluating a new antigen test. Our results also indicate that a well-chosen and validated antigen test provides excellent results in the identification of patients who are shedding viable virus (although some caveats still remain) in the screening setting of asymptomatic or mildly symptomatic individuals.Funding Statement: This research was internally funded by the Hospital Karvina-Raj and the Public Health Institute Ostrava. Antigen tests were provided by the Ministry of Health of the Czech Republic.Declaration of Interests: All Authors declare that they have no conflict of interest regarding the research presented in this paper.Ethics Approval Statement: The study was approved by the local Ethics Committee, No. NsPKar/19956/2020/SEK.

Multimorbidity Patterns of Chronic Diseases among Indonesians: Insights from Indonesian National Health Insurance (INHI) Sample Data.

Given the increasing burden of chronic diseases in Indonesia, characteristics of chronic multimorbidities have not been comprehensively explored. Therefore, this research evaluated chronic multimorbidity patterns among Indonesians using Indonesian National Health Insurance (INHI) sample data. We included 46 chronic diseases and analyzed their distributions using population-weighted variables provided in the datasets. Results showed that chronic disease patients accounted for 39.7% of total patients who attended secondary health care in 2015–2016. In addition, 43.1% of those were identified as having chronic multimorbidities. Findings also showed that multimorbidities were strongly correlated with an advanced age, with large numbers of patients and visits in all provinces, beyond those on Java island. Furthermore, hypertension was the leading disease, and the most common comorbidities were diabetes mellitus, cerebral ischemia/chronic stroke, and chronic ischemic heart disease. In addition, disease proportions for certain disease dyads differed according to age group and gender. Compared to survey methods, claims data are more economically efficient and are not influenced by recall bias. Claims data can be a promising data source in the next few years as increasing percentages of Indonesians utilize health insurance coverage. Nevertheless, some adjustments in the data structure are accordingly needed to utilize claims data for disease control and surveillance purposes.

Resistance to natural and synthetic gene drive systems.

Scientists are rapidly developing synthetic gene drive elements intended for release into natural populations. These are intended to control or eradicate disease vectors and pests, or to spread useful traits through wild populations for disease control or conservation purposes. However, a crucial problem for gene drives is the evolution of resistance against them, preventing their spread. Understanding the mechanisms by which populations might evolve resistance is essential for engineering effective gene drive systems. This review summarizes our current knowledge of drive resistance in both natural and synthetic gene drives. We explore how insights from naturally occurring and synthetic drive systems can be integrated to improve the design of gene drives, better predict the outcome of releases and understand genomic conflict in general.

On-site analysis of COVID-19 on the surfaces in wards

SARS-Cov-2 has erupted across the globe, and confirmed cases of COVID-19 pose a high infection risk. Infected patients typically receive their treatment in specific isolation wards, where they are confined for at least 14 days. The virus may contaminate any surface of the room, especially frequently touched surfaces. Therefore, surface contamination in wards should be monitored for disease control and hygiene purposes. Herein, surface contamination in the ward was detected on-site using an RNA extraction-free rapid method. The whole detection process, from surface sample collection to readout of the detection results, was finished within 45 min. The nucleic acid extraction-free method requires minimal labor. More importantly, the tests were performed on-site and the results were obtained almost in real-time. The test confirmed that 31 patients contaminated seven individual sites. Among the sampled surfaces, the electrocardiogram fingertip presented a 72.7% positive rate, indicating that this surface is an important hygiene site. Meanwhile, the bedrails showed the highest correlation with other surfaces, so should be detected daily. Another surface with high contamination risk was the door handle in the bathroom. To our knowledge, we present the first on-site analysis of COVID-19 surface contamination in wards. The results and applied technique provide a potential further reference for disease control and hygiene suggestions.

Decision tree machine learning applied to bovine tuberculosis risk factors to aid disease control decision making

Identifying and understanding the risk factors for endemic bovine tuberculosis (TB) in cattle herds is critical for the control of this disease. Exploratory machine learning techniques can uncover complex non-linear relationships and interactions within disease causation webs, and enhance our knowledge of TB risk factors and how they are interrelated. Classification tree analysis was used to reveal associations between predictors of TB in England and each of the three surveillance risk areas (High Risk, Edge, and Low Risk) in 2016, identifying the highest risk herds. The main classifying predictor for farms in England overall related to the TB prevalence in the 100 nearest cattle herds. In the High Risk and Edge areas it was the number of slaughterhouse destinations and in the Low Risk area it was the number of cattle tested in surveillance tests. How long ago the last confirmed incident was resolved was the most frequent classifier in trees; if within two years, leading to the highest risk group of herds in the High Risk and Low Risk areas. At least two different slaughterhouse destinations led to the highest risk group of herds in England, whereas in the Edge area it was a combination of no contiguous low-risk neighbours (i.e. in a 1 km radius) and a minimum proportion of 6–23 month-old cattle in November. A threshold value of prevalence in 100 nearest neighbours increased the risk in all areas, although the value was specific to each area. Having low-risk contiguous neighbours reduced the risk in the Edge and High Risk areas, whereas high-risk ones increased the risk in England overall and in the Edge area specifically. The best classification tree models informed multivariable binomial logistic regression models in each area, adding statistical inference outputs. These two approaches showed similar predictive performance although there were some disparities regarding what constituted high-risk predictors. Decision tree machine learning approaches can identify risk factors from webs of causation: information which may then be used to inform decision making for disease control purposes.

The psychology of peasant religious conversion for the purpose of disease control: The role of belief in understanding Chinese rural religious practices

This paper focuses on the religious psychology of peasants who undergo religious conversion in order to cure an illness or disease. Field research was conducted in Wang village in Northern Jiangsu, examining the psychology of newly converted peasants. In academic circles psychology of peasants is usually critiqued according to utility and rationality. In this paper, belief is a starting point for understanding the psychology of peasants. The natural mentality and family ethics of the peasants lead them to place high expectations on religion as a tool for curing disease and facing life crises and dilemmas. The three levels of religious practice include: religious construction of ‘belief’; emotional embedding of ‘belief’; and developing ‘faith’. These requirements lead to the transformation of the individual’s psychological status from secular to religious. Based on the interaction between the individual and religion which is affected by the initial disease and its seriousness, peasants’ religious psychology is divided into three types: collapse of belief; transition of belief; and upgrading of belief. The rituals and different attitudes towards belief constitute the mechanism of developing religious psychology and also shape peasants’ attitudes towards faith. In addition, this paper explores the role of belief in understanding individual religious psychology, religious conversion, and religious revival in Chinese rural religious practices.

Astaxanthin Modulation of Signaling Pathways That Regulate Autophagy.

Autophagy is a lysosomal pathway that degrades and recycles unused or dysfunctional cell components as well as toxic cytosolic materials. Basal autophagy favors cell survival. However, the aberrant regulation of autophagy can promote pathological conditions. The autophagy pathway is regulated by several cell-stress and cell-survival signaling pathways that can be targeted for the purpose of disease control. In experimental models of disease, the carotenoid astaxanthin has been shown to modulate autophagy by regulating signaling pathways, including the AMP-activated protein kinase (AMPK), cellular homolog of murine thymoma virus akt8 oncogene (Akt), and mitogen-activated protein kinase (MAPK), such as c-Jun N-terminal kinase (JNK) and p38. Astaxanthin is a promising therapeutic agent for the treatment of a wide variety of diseases by regulating autophagy.

Trust and the ethical challenges in the use of whole genome sequencing for tuberculosis surveillance: a qualitative study of stakeholder perspectives

BackgroundEmerging genomic technologies promise more efficient infectious disease control. Whole genome sequencing (WGS) is increasingly being used in tuberculosis (TB) diagnosis, surveillance, and epidemiology. However, while the use of WGS by public health agencies may raise ethical, legal, and socio-political concerns, these challenges are poorly understood.MethodBetween November 2017 and April 2018, we conducted semi-structured interviews with 22 key stakeholders across the fields of governance and policy, public health, and laboratory sciences representing the major jurisdictions currently using WGS in national TB programs. Thematic analysis of the interviews was conducted using NVivo 11.ResultsRespondents identified several ethical and practical challenges associated with WGS in TB care and surveillance, all related to issues of trust, including: 1) the power of public health; 2) data sharing and profits derived from surveillance efforts; and 3) concerns regarding who has access to, and can benefit from, the technology. Additional challenges included: the potential utility that WGS adds to a public health program, the risks associated with linking necessary epidemiological metadata to the genomic data, and challenges associated with jurisdictional capacity to implement the technology.ConclusionsSuccessful implementation of WGS is dependent on fostering relationships of trust between those working with genomics technology and those directly impacted by it, including clinicians. Building trust (a) between the public and the public health agencies and (b) within public health agencies themselves is critical due to the inherent complexity of WGS and its implementation for communicable disease control purposes.