ABSTRACT
Wastewater-based epidemiology (WBE) is a promising technique for monitoring the rapidly increasing use of antiviral drugs during the COVID-19 pandemic. It is essential to evaluate the in-sewer stability of antiviral drugs in order to determine appropriate biomarkers. This study developed an analytical method for quantification of 17 typical antiviral drugs, and investigated the stability of target compounds in sewer through 4 laboratory-scale gravity sewer reactors. Nine antiviral drugs (lamivudine, acyclovir, amantadine, favipiravir, nevirapine, oseltamivir, ganciclovir, emtricitabine and telbivudine) were observed to be stable and recommended as appropriate biomarkers for WBE. As for the other 8 unstable drugs (abacavir, arbidol, ribavirin, zidovudine, ritonavir, lopinavir, remdesivir and efavirenz), their attenuation was driven by adsorption, biodegradation and diffusion. Moreover, reaction kinetics revealed that the effects of sediments and biofilms were regarded to be independent in gravity sewers, and the rate constants of removal by biofilms was directly proportional to the ratio of surface area against wastewater volume. The study highlighted the potential importance of flow velocity for compound stability, since an increased flow velocity significantly accelerated the removal of unstable biomarkers. In addition, a framework for graded evaluation of biomarker stability was proposed to provide reference for researchers to select suitable WBE biomarkers. Compared with current classification method, this framework considered the influences of residence time and different removal mechanisms, which additionally screened four antiviral drugs as viable WBE biomarkers. This is the first study to report the stability of antiviral drugs in gravity sewers.
Subject(s)
COVID-19 , Water Pollutants, Chemical , Humans , Sewage , Wastewater-Based Epidemiological Monitoring , Antiviral Agents , Pandemics , Water Pollutants, Chemical/analysis , BiomarkersABSTRACT
On January 31, 2020, the U.S. Department of Health and Human Services (HHS) declared, under Section 319 of the Public Health Service Act, a U.S. public health emergency because of the emergence of a novel virus, SARS-CoV-2.* After 13 renewals, the public health emergency will expire on May 11, 2023. Authorizations to collect certain public health data will expire on that date as well. Monitoring the impact of COVID-19 and the effectiveness of prevention and control strategies remains a public health priority, and a number of surveillance indicators have been identified to facilitate ongoing monitoring. After expiration of the public health emergency, COVID-19-associated hospital admission levels will be the primary indicator of COVID-19 trends to help guide community and personal decisions related to risk and prevention behaviors; the percentage of COVID-19-associated deaths among all reported deaths, based on provisional death certificate data, will be the primary indicator used to monitor COVID-19 mortality. Emergency department (ED) visits with a COVID-19 diagnosis and the percentage of positive SARS-CoV-2 test results, derived from an established sentinel network, will help detect early changes in trends. National genomic surveillance will continue to be used to estimate SARS-CoV-2 variant proportions; wastewater surveillance and traveler-based genomic surveillance will also continue to be used to monitor SARS-CoV-2 variants. Disease severity and hospitalization-related outcomes are monitored via sentinel surveillance and large health care databases. Monitoring of COVID-19 vaccination coverage, vaccine effectiveness (VE), and vaccine safety will also continue. Integrated strategies for surveillance of COVID-19 and other respiratory viruses can further guide prevention efforts. COVID-19-associated hospitalizations and deaths are largely preventable through receipt of updated vaccines and timely administration of therapeutics (1-4).
Subject(s)
COVID-19 , Sentinel Surveillance , Humans , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Testing , COVID-19 Vaccines , Public Health , SARS-CoV-2 , United States/epidemiology , Wastewater-Based Epidemiological MonitoringABSTRACT
In year one of the COVID-19 epidemic, the incidence of infection for US carceral populations was 5.5-fold higher than that in the community. Prior to the rapid roll out of a comprehensive jail surveillance program of Wastewater-Based Surveillance (WBS) and individual testing for SARS-CoV-2, we sought the perspectives of formerly incarcerated individuals regarding mitigation strategies against COVID-19 to inform acceptability of the new program. In focus groups, participants discussed barriers to their receiving COVID-19 testing and vaccination. We introduced WBS and individual nasal self-testing, then queried if wastewater testing to improve surveillance of emerging outbreaks before case numbers surged, and specimen self-collection, would be valued. The participants' input gives insight into ways to improve the delivery of COVID-19 interventions. Hearing the voices of those with lived experiences of incarceration is critical to understanding their views on infection control strategies and supports including justice-involved individuals in decision-making processes regarding jail-based interventions.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , COVID-19/epidemiology , COVID-19/prevention & control , Wastewater , Jails , Wastewater-Based Epidemiological Monitoring , COVID-19 TestingABSTRACT
Wastewater surveillance is considered a promising approach for COVID-19 surveillance in communities. In this study, we collected wastewater samples between November 2020 and February 2022 from twenty-three sites in the Bangkok Metropolitan Region to detect the presence of SARS-CoV-2 and its variants for comparison to standard clinical sampling. A total of 215 wastewater samples were collected and tested for SARS-CoV-2 RNA by real-time PCR with three targeted genes (N, E, and ORF1ab); 102 samples were positive (42.5%). The SARS-CoV-2 variants were determined by a multiplex PCR MassARRAY assay to distinguish four SARS-CoV-2 variants, including Alpha, Beta, Delta, and Omicron. Multiple variants of Alpha-Delta and Delta-Omicron were detected in the wastewater samples in July 2021 and January 2022, respectively. These wastewater variant results mirrored the country data from clinical specimens deposited in GISAID. Our results demonstrated that wastewater surveillance using multiple signature mutation sites for SARS-CoV-2 variant detection is an appropriate strategy to monitor the presence of SARS-CoV-2 variants in the community at a low cost and with rapid turn-around time. However, it is essential to note that sequencing surveillance of wastewater samples should be considered complementary to whole genome sequencing of clinical samples to detect novel variants.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , COVID-19/diagnosis , COVID-19/epidemiology , RNA, Viral/genetics , Wastewater , Wastewater-Based Epidemiological Monitoring , ThailandABSTRACT
Wastewater-based epidemiology (WBE) has become a valuable tool for monitoring SARS-CoV-2 infection trends throughout the COVID-19 pandemic. Population biomarkers that measure the relative human fecal contribution to normalize SARS-CoV-2 wastewater concentrations are needed for improved analysis and interpretation of community infection trends. The Centers for Disease Control and Prevention National Wastewater Surveillance System (CDC NWSS) recommends using the wastewater flow rate or human fecal indicators as population normalization factors. However, there is no consensus on which normalization factor performs best. In this study, we provided the first multistate assessment of the effects of flow rate and human fecal indicators (crAssphage, F+ Coliphage, and PMMoV) on the correlation of SARS-CoV-2 wastewater concentrations and COVID-19 cases using the CDC NWSS dataset of 182 communities across six U.S. states. Flow normalized SARS-CoV-2 wastewater concentrations produced the strongest correlation with COVID-19 cases. The correlation from the three human fecal indicators were significantly lower than flow rate. Additionally, using reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) significantly improved correlation values over samples that were analyzed with real-time reverse transcription quantitative polymerase chain reaction (rRT-qPCR). Our assessment shows that utilizing flow normalization with RT-ddPCR generate the strongest correlation between SARS-CoV-2 wastewater concentrations and COVID-19 cases.
Subject(s)
COVID-19 , United States/epidemiology , Humans , COVID-19/epidemiology , SARS-CoV-2 , Wastewater , Wastewater-Based Epidemiological Monitoring , Pandemics , Real-Time Polymerase Chain Reaction , RNA, ViralABSTRACT
Wastewater surveillance and quantitative analysis of SARS-CoV-2 RNA are increasingly used to monitor the spread of COVID-19 in the community. We studied the feasibility of applying the surveillance data for early detection of local outbreaks. A Monte Carlo simulation model was constructed, applying data on reported variation in RNA gene copy concentration in faeces and faecal masses shed. It showed that, even with a constant number of SARS-CoV-2 RNA shedders, the variation in concentrations found in wastewater samples will be large, and that it will be challenging to translate viral concentrations into incidence estimates, especially when the number of shedders is low. Potential signals for early detection of hypothetical outbreaks were analysed for their performance in terms of sensitivity and specificity of the signals. The results suggest that a sudden increase in incidence is not easily identified on the basis of wastewater surveillance data, especially in small sampling areas and in low-incidence situations. However, with a high number of shedders and when combining data from multiple consecutive tests, the performance of wastewater sampling is expected to improve considerably. The developed modelling approach can increase our understanding of the results from wastewater surveillance of SARS-CoV-2.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , COVID-19/epidemiology , Feasibility Studies , RNA, Viral , Wastewater , Wastewater-Based Epidemiological Monitoring , Disease OutbreaksSubject(s)
Communicable Diseases , Environmental Monitoring , Wastewater-Based Epidemiological Monitoring , Wastewater , Humans , Communicable Diseases/diagnosis , Communicable Diseases/epidemiology , Wastewater/analysis , Wastewater/microbiology , Wastewater/parasitology , Wastewater/virology , Environmental Monitoring/methods , Biological Monitoring/methodsABSTRACT
International airports can have a key role in screening, detecting, and mitigating cross-border transmission of SARS-CoV-2 and potentially other infectious diseases. With aircraft passengers representing a subpopulation of a country or region, aircraft-based wastewater surveillance can be a promising approach to effectively identifying emerging viruses, tracing their evolution, and mapping global spread with international flights. Therefore, we propose the development of a global aircraft-based wastewater genomic surveillance network, with the busiest international airports as central nodes and continuing air travel journeys as vectors. This surveillance programme requires routinely collecting aircraft wastewater samples for microbiological analysis and sequencing and linking the resulting data with associated international air traffic information. With the creation of a strong international alliance between the airline industry and health authorities, this surveillance network will potentially complement public health systems with a true early warning ability to inform decision making for new variants and future global health risks.
Subject(s)
COVID-19 , Wastewater , Humans , Travel , Wastewater-Based Epidemiological Monitoring , Pandemics/prevention & control , COVID-19/epidemiology , COVID-19/prevention & control , SARS-CoV-2/genetics , Aircraft , GenomicsABSTRACT
SARS-CoV-2 surveillance of viral populations in wastewater samples is recognized as a useful tool for monitoring epidemic waves and boosting health preparedness. Next generation sequencing of viral RNA isolated from wastewater is a convenient and cost-effective strategy to understand the molecular epidemiology of SARS-CoV-2 and provide insights on the population dynamics of viral variants at the community level. However, in low- and middle-income countries, isolated groups have performed wastewater monitoring and data has not been extensively shared in the scientific community. Here we report the results of monitoring the co-circulation and abundance of variants of concern (VOCs) of SARS-CoV-2 in Uruguay, a small country in Latin America, between November 2020-July 2021 using wastewater surveillance. RNA isolated from wastewater was characterized by targeted sequencing of the Receptor Binding Domain region within the spike gene. Two computational approaches were used to track the viral variants. The results of the wastewater analysis showed the transition in the overall predominance of viral variants in wastewater from No-VOCs to successive VOCs, in agreement with clinical surveillance from sequencing of nasal swabs. The mutations K417T, E484K and N501Y, that characterize the Gamma VOC, were detected as early as December 2020, several weeks before the first clinical case was reported. Interestingly, a non-synonymous mutation described in the Delta VOC, L452R, was detected at a very low frequency since April 2021 when using a recently described sequence analysis tool (SAM Refiner). Wastewater NGS-based surveillance of SARS-CoV-2 is a reliable and complementary tool for monitoring the introduction and prevalence of VOCs at a community level allowing early public health decisions. This approach allows the tracking of symptomatic and asymptomatic individuals, who are generally under-reported in countries with limited clinical testing capacity. Our results suggests that wastewater-based epidemiology can contribute to improving public health responses in low- and middle-income countries.
Subject(s)
COVID-19 , Wastewater , Humans , SARS-CoV-2/genetics , Wastewater-Based Epidemiological Monitoring , COVID-19/epidemiology , Genomics , High-Throughput Nucleotide SequencingABSTRACT
Wastewater-based epidemiology has been used extensively throughout the COVID-19 (coronavirus disease 19) pandemic to detect and monitor the spread and prevalence of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) and its variants. It has proven an excellent, complementary tool to clinical sequencing, supporting the insights gained and helping to make informed public-health decisions. Consequently, many groups globally have developed bioinformatics pipelines to analyse sequencing data from wastewater. Accurate calling of mutations is critical in this process and in the assignment of circulating variants; yet, to date, the performance of variant-calling algorithms in wastewater samples has not been investigated. To address this, we compared the performance of six variant callers (VarScan, iVar, GATK, FreeBayes, LoFreq and BCFtools), used widely in bioinformatics pipelines, on 19 synthetic samples with known ratios of three different SARS-CoV-2 variants of concern (VOCs) (Alpha, Beta and Delta), as well as 13 wastewater samples collected in London between the 15th and 18th December 2021. We used the fundamental parameters of recall (sensitivity) and precision (specificity) to confirm the presence of mutational profiles defining specific variants across the six variant callers. Our results show that BCFtools, FreeBayes and VarScan found the expected variants with higher precision and recall than GATK or iVar, although the latter identified more expected defining mutations than other callers. LoFreq gave the least reliable results due to the high number of false-positive mutations detected, resulting in lower precision. Similar results were obtained for both the synthetic and wastewater samples.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , COVID-19/epidemiology , Wastewater-Based Epidemiological Monitoring , Wastewater , AlgorithmsABSTRACT
The ongoing COVID-19 pandemic has emphasized the significance of wastewater surveillance in monitoring and tracking the spread of infectious diseases, including SARS-CoV-2. The wastewater surveillance approach detects genetic fragments from viruses in wastewater, which could provide an early warning of outbreaks in communities. In this study, we determined the concentrations of four types of endogenous viruses, including non-enveloped DNA (crAssphage and human adenovirus 40/41), non-enveloped RNA (enterovirus), and enveloped RNA (SARS-CoV-2) viruses, from wastewater samples using the adsorption-extraction (AE) method with electronegative HA membranes of different pore sizes (0.22, 0.45, and 0.80 µm). Our findings showed that the membrane with a pore size of 0.80 µm performed comparably to the membrane with a pore size of 0.45 µm for virus detection/quantitation (repeated measurement one-way ANOVA; p > 0.05). We also determined the recovery efficiencies of indigenous crAssphage and pepper mild mottle virus, which showed recovery efficiencies ranging from 50% to 94% and from 20% to 62%, respectively. Our results suggest that the use of larger pore size membranes may be beneficial for processing larger sample volumes, particularly for environmental waters containing low concentrations of viruses. This study offers valuable insights into the application of the AE method for virus recovery from wastewater, which is essential for monitoring and tracking infectious diseases in communities.
Subject(s)
COVID-19 , Viruses , Humans , Wastewater , SARS-CoV-2/genetics , Pandemics , Adsorption , Wastewater-Based Epidemiological Monitoring , RNA , RNA, ViralABSTRACT
Wastewater-based epidemiology (WBE) is a non-invasive and cost-effective approach for monitoring the spread of a pathogen within a community. WBE has been adopted as one of the methods to monitor the spread and population dynamics of the SARS-CoV-2 virus, but significant challenges remain in the bioinformatic analysis of WBE-derived data. Here, we have developed a new distance metric, CoVdist, and an associated analysis tool that facilitates the application of ordination analysis to WBE data and the identification of viral population changes based on nucleotide variants. We applied these new approaches to a large-scale dataset from 18 cities in nine states of the USA using wastewater collected from July 2021 to June 2022. We found that the trends in the shift between the Delta and Omicron SARS-CoV-2 lineages were largely consistent with what was seen in clinical data, but that wastewater analysis offered the added benefit of revealing significant differences in viral population dynamics at the state, city, and even neighborhood scales. We also were able to observe the early spread of variants of concern and the presence of recombinant lineages during the transitions between variants, both of which are challenging to analyze based on clinically-derived viral genomes. The methods outlined here will be beneficial for future applications of WBE to monitor SARS-CoV-2, particularly as clinical monitoring becomes less prevalent. Additionally, these approaches are generalizable, allowing them to be applied for the monitoring and analysis of future viral outbreaks.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , United States/epidemiology , SARS-CoV-2/genetics , COVID-19/epidemiology , Wastewater , Wastewater-Based Epidemiological MonitoringABSTRACT
In this long-term study (eight months), a wastewater-based epidemiology program was initiated as a decision support tool for the detection and containment of COVID-19 spread in the Technion campus. The on-campus students' accommodations (â¼3,300 residents) were divided into housing clusters and monitored through wastewater SARS-CoV-2 surveillance in 10 manholes. Results were used to create a 'traffic-light' scheme allowing the Technion's COVID-19 task force to track COVID-19 spatiotemporal spread on the campus, and consequently, contain it before high morbidity levels develop. Of the 523 sewage samples analysed, 87.4% were negative for SARS-CoV-2 while 11.5% were positive, corroborating morbidity information the COVID-19 task force had. For 7.6% of the SARS-CoV-2 positive samples, the task force had no information about positive resident/s. In these events, new cases were identified after the relevant residents were clinically surge tested for COVID-19. Hence, in these instances, wastewater surveillance provided early warning helping to secure the health of the campus residents by minimising COVID-19 spread. The inflammation biomarker ferritin levels in SARS-CoV-2 positive sewage samples were significantly higher than in negative ones. This may indicate that in the future, ferritin (and other biomarkers) concentrations in wastewater could serve as indicators of infectious and inflammatory disease outbreaks.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , COVID-19/epidemiology , Wastewater , Wastewater-Based Epidemiological Monitoring , Sewage , Disease Outbreaks , FerritinsABSTRACT
Candida auris transmission is steadily increasing across the United States. We report culture-based detection of C. auris in wastewater and the epidemiologic link between isolated strains and southern Nevada, USA, hospitals within the sampled sewershed. Our results illustrate the potential of wastewater surveillance for containing C. auris.
Subject(s)
Candida , Candidiasis , Humans , United States/epidemiology , Candidiasis/drug therapy , Candida auris , Wastewater , Nevada/epidemiology , Wastewater-Based Epidemiological Monitoring , Disease Outbreaks , Antifungal Agents/therapeutic useABSTRACT
Wastewater surveillance plays an important role in the management of the coronavirus disease 2019 (COVID-19) pandemic all over the world. Using different wastewater collection points in Leuven, we wanted to investigate the use of wastewater surveillance as an early warning system for an uprise of infections and as a tool to follow the circulation of specific variants of concern (VOCs) in particular geographic areas. Wastewater samples were collected from local neighborhood sewers and from a large regional wastewater treatment plant (WWTP) in the area of Leuven, Belgium. After virus concentration, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA was quantified by real-time quantitative polymerase chain reaction (RT-qPCR) and normalized with the human fecal indicator pepper mild mottle virus (PMMoV). A combination of multiplex RT-qPCR assays was used to detect signature mutations of circulating VOCs. Fecal virus shedding of SARS-CoV-2 variants was measured in feces samples of hospitalized patients. In two residential sampling sites, a rise in wastewater SARS-CoV-2 concentration preceded peaks in positive cases. In the WWTP, viral load peaks were seen concomitant with the consecutive waves of positive cases caused by the original Wuhan SARS-CoV-2 strain and subsequent VOCs. During the Omicron BA.1 wave, the wastewater viral load increased to a lesser degree, even after normalization of SARS-CoV-2 concentration using PMMoV. This might be attributable to a lower level of fecal excretion of this variant. Circulation of SARS-CoV-2 VOCs Alpha, Delta, Omicron BA1/BA.2, and BA.4/BA.5 could be detected based on the presence of specific key mutations. The shift in variants was noticeable in the wastewater, with key mutations of two different variants being present simultaneously during the transition period. Wastewater-based surveillance is a sensitive tool to monitor SARS-CoV-2 circulation levels and VOCs in larger regions. In times of reduced test capacity, this can prove to be highly valuable. Differences in excretion levels of various SARS-CoV-2 variants should however be taken into account when using wastewater surveillance to monitor SARS-CoV-2 circulation levels in the population.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Belgium , Wastewater , Wastewater-Based Epidemiological Monitoring , RNA, ViralABSTRACT
We consider the dynamics of a virus spreading through a population that produces a mutant strain with the ability to infect individuals that were infected with the established strain. Temporary cross-immunity is included using a time delay, but is found to be a harmless delay. We provide some sufficient conditions that guarantee local and global asymptotic stability of the disease-free equilibrium and the two boundary equilibria when the two strains outcompete one another. It is shown that, due to the immune evasion of the emerging strain, the reproduction number of the emerging strain must be significantly lower than that of the established strain for the local stability of the established-strain-only boundary equilibrium. To analyze the unique coexistence equilibrium we apply a quasi steady-state argument to reduce the full model to a two-dimensional one that exhibits a global asymptotically stable established-strain-only equilibrium or global asymptotically stable coexistence equilibrium. Our results indicate that the basic reproduction numbers of both strains govern the overall dynamics, but in nontrivial ways due to the inclusion of cross-immunity. The model is applied to study the emergence of the SARS-CoV-2 Delta variant in the presence of the Alpha variant using wastewater surveillance data from the Deer Island Treatment Plant in Massachusetts, USA.
Subject(s)
COVID-19 , Deer , Humans , Animals , Wastewater , Wastewater-Based Epidemiological Monitoring , COVID-19/epidemiology , SARS-CoV-2/geneticsABSTRACT
The novel coronavirus SARS-CoV-2 has spread at an unprecedented rate since late 2019, leading to the global COVID-19 pandemic. During the pandemic, being able to detect SARS-CoV-2 in human populations with high coverage quickly is a huge challenge. As SARS-CoV-2 is excreted in human excreta and thus exposed to the aqueous environment through sewers, the goal is to develop an ideal, non-invasive, cost-effective epidemiological method for detecting SARS-CoV-2. Wastewater surveillance has gained widespread interest and is increasingly being investigated as an effective early warning tool for monitoring the spread and evolution of the virus. This review emphasizes important findings on SARS-CoV-2 wastewater-based epidemiology (WBE) in different continents and techniques used to detect SARS-CoV-2 in wastewater during the period 2020-2022. The results show that WBE is a valuable population-level method for monitoring SARS-CoV-2 and is a valuable early warning alert. It can assist policymakers in formulating relevant policies to avoid the negative impacts of early or delayed action. Such strategy can also help avoid unnecessary wastage of medical resources, rationalize vaccine distribution, assist early detection, and contain large-scale outbreaks.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , COVID-19/epidemiology , Wastewater , Pandemics , Wastewater-Based Epidemiological MonitoringABSTRACT
The paper discusses the implementation of Hong Kong's tailor-made sewage surveillance programme led by the Government, which has demonstrated how an efficient and well-organized sewage surveillance system can complement conventional epidemiological surveillance to facilitate the planning of intervention strategies and actions for combating COVID-19 pandemic in real-time. This included the setting up of a comprehensive sewerage network-based SARS-CoV-2 virus surveillance programme with 154 stationary sites covering 6 million people (or 80 % of the total population), and employing an intensive monitoring programme to take samples from each stationary site every 2 days. From 1 January to 22 May 2022, the daily confirmed case count started with 17 cases per day on 1 January to a maximum of 76,991 cases on 3 March and dropped to 237 cases on 22 May. During this period, a total of 270 "Restriction-Testing Declaration" (RTD) operations at high-risk residential areas were conducted based on the sewage virus testing results, where over 26,500 confirmed cases were detected with a majority being asymptomatic. In addition, Compulsory Testing Notices (CTN) were issued to residents, and the distribution of Rapid Antigen Test kits was adopted as alternatives to RTD operations in areas of moderate risk. These measures formulated a tiered and cost-effective approach to combat the disease in the local setting. Some ongoing and future enhancement efforts to improve efficacy are discussed from the perspective of wastewater-based epidemiology. Forecast models on case counts based on sewage virus testing results were also developed with R2 of 0.9669-0.9775, which estimated that up to 22 May 2022, around 2,000,000 people (~67 % higher than the total number of 1,200,000 reported to the health authority, due to various constraints or limitations) had potentially contracted the disease, which is believed to be reflecting the real situation occurring in a highly urbanized metropolis like Hong Kong.