Back to Main Page

June 1^st, 2004

Ministry of Health and National Science Council, TAIWAN

1.

SARS Outbreak, Taiwan, 2003, Emerging Infectious Diseases, 2004; 10(2): 201-206

Ying-Hen Hsieh,* Cathy W.S. Chen,† and Sze-Bi Hsu‡

*National Chung Hsing University, Taichung, Taiwan

†Feng Chia University, Taichung, Taiwan

‡National Tsing Hua University, Hsinchu, Taiwan

We studied the severe acute respiratory syndrome (SARS) outbreak in Taiwan, using the daily case-reporting data from May 5 to June 4 to learn how it had spread so rapidly. Our results indicate that most SARS-infected persons had symptoms and were admitted before their infections were reclassified as probable cases. This finding could indicate efficient admission, slow reclassification process, or both. The high percentage of nosocomial infections in Taiwan suggests that infection from hospitalized patients with suspected, but not yet classified, cases is a major factor in the spread of disease. Delays in reclassification also contributed to the problem. Because accurate diagnostic testing for SARS is currently lacking, intervention measures aimed at more efficient diagnosis, isolation of suspected SARS patients, and reclassification procedures could greatly reduce the number of infections in future outbreaks.

2.

Re: Mathematical Modeling of SARS: Cautious in All Our Movements, Journal of Epidemiology and Community Health, (18 November 2003)

Ying-Hen Hsieh,* and Cathy W.S. Chen†

*National Chung Hsing University, Taichung, Taiwan

†Feng Chia University, Taichung, Taiwan

Dear Editor

Dr Nishiura [1] accentuated that caution must be exercised in using mathematical models to ascertain the recent SARS epidemics.

The key issue, as we believe, is to understand the model and its results for what they are and, more importantly, for what they are not. It is especially true with the basic reproductive number R0, or its variant the effective reproductive number at time t Rt, which has been estimated for the recent SARS outbreaks in Beijing, Hong Kong,, Toronto, Taiwan, and Singapore in several recent articles (e.g. [2-6]). R0, the average number of secondary infections caused by an infective person upon entering a totally susceptible population, is a useful tool to gauge the initial trend of an epidemic. It is also often misunderstood and misused. Indeed, a recent news feature in Nature [7] described the basic reproductive number R0 as "A measure of a disease's infectiousness" corresponds to how many people, on average, are infected by each patient in the absence of any control measures, which erroneously left out the important requirement that the patient must be an index case in that population, i.e. all possible contacts of that person are susceptible to infection.

The effective reproductive number at time t Rt =R0 x(t), where x is the susceptible proportion of population at time t, measures number of infections caused by a new case at time t.[3] It is more important as a mean to understand the progression of the epidemic, taking into consideration the control measures, behavior changes, and climate as they have all been proven to be important in the case of SARS. Moreover, one can approximate the average growth rate of an epidemic over a given time interval while the epidemic is underway from the cumulative case data. From which one could then estimate the "mean effective reproductive number of the observed time period" R*, i.e. the average number of secondary infections caused by one infective person during the observed time interval. The precise definition gives the public officials a clear chronology of progression (or cessation) of the epidemic, albeit retrospectively.

For illustration, we used the cumulative number of probable SARS cases in Taiwan by onset date from March 12 to June 15,[8] exponential curve fitting with first-order autocorrelation in the error structure,[9] and the period of SARS infectivity of 29.03 days (i.e. time from onset to death or discharge) estimated from [10] to obtain the mean effective reproductive numbers for the five distinct periods during March 12 - June 15 (Table 1). A chronology of relevant events of importance is given as a footnote of Table 1. Figure 1 paints a clear picture of slowly growing epidemic in the beginning, to the outbreak kindled by the admission of first SARS patient to Ho Ping Hospital, the site of first hospital cluster infections, on April 9. The peak period of infections (4/11-4/26) ended with the shutdown of Ho Ping Hospital on April 24. The series of hospital clusters in Taipei and subsequently in the southern port city of Kaohsiung finally subsided with the May 11 shutdown of Chang Gung Hospital in Kaohsiung, due to successful intervention efforts to stop nosocomial infections, the last of which occurred shortly before June 9 the onset date of the last hospital infection in Taiwan. The result clearly points to the important lesson from the outbreak in Taiwan shutdown of hospitals where cluster infections have occurred had been a crucial step in breaking the local chains of transmissions. The effect of quarantine measures, however, is less clear and requires further study, perhaps with mathematical modeling. Clearly, retrospective mathematical modeling is an important reference for public health policy makers intending to contain possible future outbreaks with the most effective intervention measures as long as we understand them for what they are and what they are not.

Table 1 Mean effective reproductive numbers R* for each of the five time periods with events of relevance during the time periods

3/18 ? Implementation of Level A quarantine.
4/09 ? Admission of first SARS patient to Ho Ping Hospital.
4/24 ? Shutdown of Ho Ping Hospital.
4/28 ? Implementation of Level B quarantine.
5/11 ? Shutdown of Chang Gung Hospital.
6/15 ? Onset date of the last hospital infection.

References:

(1) Nishiura H. Mathematical modeling of SARS: cautious in all our movements. J Epidem Com Health 2003; In Press.

(2) Riley S, Fraser C, Donnelly C, Ghani AC, Abu-Raddad LJ, Hedley AJ, et al. Transmission dynamics of the etiological agents of SARS in Hong Kong: Impact of public health interventions. Science 2003; 300: 961-66 (20 June 2003) Published online 23 May 2003 (10.1126/science.1086478)

(3) Lipsitch, M, Cohen T, Cooper B, Robins JM, Ma S, James L, et al. Transmission dynamics and control of severe acute respiratory syndrome. Science 2003; 300: 1966-70 (20 June 2003) Published online 23 May 2003; 10.1126/science.1086616

(4) Zhou G, & Yan G. Severe Acute Respiratory Syndrome epidemics in Asia. Emerg Infect Dis 2003; 9(12), In Press.

(5) Hsieh YH, Chen CWS, & Hsu SB. The Severe Acute Respiratory Syndrome outbreak in Taiwan: Lessons to be learned. Emerg Infect Dis 2003; To Appear.

(6) Chowell G, Fenimore PW, Castillo-Garsow MA, & Castillo-Chavez C. SARS outbreaks in Ontario, Hong Kong, and Singapore: the role of diagnosis and isolation as a control mechanism. J Theoret Biol 2003; 224: 1-8.

(7) Pearson H, Clarke T, Abbott A, Knight J, & Cyranoski D. SARS: what have we learned? Nature 2003; 424(6945):121-6. Nature 424, 121: 126(2003) (10 July 2003).

(8) Center for Disease Control (Taiwan). Available at http://www.cdc.gov.tw/sarsen

(9) Hsieh YH,. & Chen CWS. Severe Acute Respiratory Syndrome: Numbers don’t tell the whole story. British Medical J 2003; 326: 1395-1396.

(10) Donnelly C, Ghani AC, Leung GM, Hedley AJ, Fraser c, Riley S, et al. Epidemiological determinants of spread of causal agent of severe acute respiratory syndrome in Hong Kong. Lancet 2003; 361(9371): 1761-66. (May 24 2003) Available at http://image.thelancet.com/extras/-3art4453web.pdf.

3.

SARS and the Internet, The New England Journal of Medicine, 2003; 349(7): 711-712

Ying-Hen Hsieh

National Chung Hsing University, Taichung 402, Taiwan

TO THE EDITOR:

Your editorial (May 15 issue)¹ describes the speed and power of the Internet in communicating to the world knowledge about severe acute respiratory syndrome (SARS) and the progression of the epidemic. This access is indispensable to those of us in Taiwan, from government officials to basic researchers like me. Because of Taiwan’s exclusion from the World Health Organization (WHO),² we had to rely solely on the Internet to obtain information about SARS from the WHO’s Web site and other Web sites like that of the Journal, until a team of epidemiologists from the WHO finally arrived in May to assess the damage here. Inexperienced at containing an outbreak, Taiwan was ill prepared for the task, and the deficiencies in hospital management and the health system were exposed. Since late April, a series of clusters of infections in hospitals made Taiwan’s “the most rapidly growing outbreak,” ³ although the pace slowed after mid-May (Fig. 1). It was said that no single entity can manage SARS on its own. ⁴ For a while, Taiwan was asked by the world to do just that.

References:

1. Drazen JM, Campion EW. SARS, the Internet, and the Journal. N Engl J Med 2003;348:2029.

2. Hsieh YH. Politics hindering SARS work. Nature 2003;423:381.

3. Update 59 — report on Guangxi (China) visit, situation in Taiwan, risk of SARS transmission during air travel. Geneva: World Health Organization, May 2003. (Accessed July 24, 2003, at http:// www.who.int/csr/sars/archive/2003_05_19/en/.)

4. Update 58 — first global consultation on SARS epidemiology, travel recommendations for Hebei Province (China), situation in Singapore. Geneva: World Health Organization, May 2003. (Accessed July 24, 2003, at http://www.who.int/csr/sars/archive/ 2003_05_17/en/.)

DRS. DRAZEN AND CAMPION REPLY:

It is essential that we learn from the worldwide experience in containing the outbreaks of SARS. This coronavirusassociated infection could reemerge as a threat to world health. The global threat required consistent responses, regardless of all our differences. The Internet facilitated rapid, global communication of information about outbreaks and the containment procedures, which were basically the same in every country. One lesson to remember is that with an infectious disease such as SARS, the welfare of all depends on early detection of the disease and open, honest communication among health officials everywhere.

Jeffrey M. Drazen, M.D.

Edward W. Campion, M.D.

4.

On SARS Epidemiology, Cumulative Case Curve, and Logistic-Type Model: Ascertaining Effectiveness of Intervention and Predicting Case Number, Emerging Infectious Diseases (in press)

Ying-Hen Hsieh,* Jen-Yu Lee,* and Hsiao-Ling Chang#

*Department of Applied Mathematics, National Chung Hsing University, Taichung, Taiwan

#Center for Disease Control, Department of Health, Taipei, Taiwan

To the Editor: The quantitative assessment of the effectiveness of public health intervention measures during the recent SARS pandemic presents a difficult challenge for modelers of infectious disease epidemiology (1-4). Zhou and Yan (5) used Richards model, a logistic-type model, to fit the cumulative number of SARS cases reported daily in Singapore, Hong Kong and Beijing, all with very encouraging result. However, the key to making use of mathematical models for SARS epidemiology is to understand the models for what they are and what they are not (6). There are two issues that one must address regarding the modeling in (5). First, they described the function F(S) in the model as measuring “the effectiveness of intervention measures”. It is important to know that the parameters in F(S), namely the maximum cases load K and the exponent of deviation a, depict the actual progression of the epidemic as described by the data used. In other words, they merely quantify the end results of whatever intervention measures that had actually been implemented during the outbreaks. Simply put, they do not shed any light on the all-important question of “what if”. Unfortunately, to gauge the effectiveness of intervention measures, one would need to consider a more complicated model with variable maximum case load and growth rate (r) to highlight the time-varying nature of an epidemic and its dependence on the intervention measures that had been implemented during the epidemic.

The second issue involves the more subtle, but nonetheless important, question of how cumulative case numbers can be most appropriately used in infectious disease epidemiology. Attempt to predict future trend of an epidemic from limited data during early stages of the epidemic is indeed futile and sometimes misleading [7]. Paradoxically, early prediction of the magnitude of an epidemic outbreak is immeasurably more important than retrospective studies. The question then is: how early is too early? It is intuitive that cumulative case curve will always exhibit S-shape curve, well-described by a logistic-type model. The essential factor one needs to consider is the time when the inflection of the cumulative case curve occurs, i.e. the moment when rapid increase in case number is replaced by slow increase. Since the inflection point, denoted by tm in (5), dictates the point in time when the rate of increase of cumulative case number reaches its maximum, the moment marks the key turning point when the spread of the disease starts to alleviate. As long as the data one uses include this infection point and a time interval shortly after, the curve fitting and the prediction of future case number will not be far from accurate.

To illustrate our point more precisely, we make use of the cumulative SARS case data by onset date in Taiwan obtained from the SARS databank of CDC, Taiwan. The data cover the time period from February 25, 2003, the onset date of first confirmed SARS case, to June 15, 2003, the onset date of last confirmed case, for a total of 346 confirmed SARS cases during the 2003 outbreak in Taiwan [8]. We fit the cumulative case data to the cumulative case function S(t) in Richards model with the initial time t0=0 being February 25 and the initial case number S0=S(0)=1. Description of the model, as well as the result of the parameter estimation, is given in the Appendix. The estimates for the parameters are r=0.136 (95% C.I.: 0.121-0.150), K=343.4 (95% C.I.: 339.7-347.1), a=1.07 (95% C.I.: 0.80-1.35), and the infection point at tm=66.62 (95%C.I.: 63.9-69.3) with adjusted r2>0.998, p<0.0001 for the goodness-of-fit of the model (Figure 1). The result indicates that the infection occurred on May 3 and the estimate for the maximum case number K=343.3 is merely 0.8% off the actual total case number.

Moreover, the case number data used is by onset date. Given a mean SARS incubation period of 5 days (4-6 days in [9]), we could backtrack the infection point for SARS infections in Taiwan to five days before May 3, namely on April 28. It is worthwhile to note that on April 26, the first SARS casualty in Taiwan past away, amid public shock and panic. Starting April 28, the government implemented a series of strict intervention measures, including household quarantine of all travellers from affected areas [10]. In retrospect, April 28 was indeed the turning point of the SARS outbreak in Taiwan.

To address the important question of making projections during an ongoing epidemic, we use the same data set but for various time intervals all starting from February 25 but truncated at various dates around the inflection point of May 3. The resulting parameter estimates are given in Table 1 of the Appendix. For the truncated data ending on April 28 before the inflection occurred, we obtain a completely unreasonable estimate of K=875.8. However, if we use the data ending on May 5, May 10, May 15, and May 20, respectively, we obtain the respective estimates of K=204.9, 253.1, 334.2, and 342.1. The estimate clearly improves as we move further past the inflection time of May 3 (Figure 2). Moreover, the last estimate, using data from February 25-May 20 only, produces a mere 1.1% error from the eventual cumulative case number of 346, with 95% C.I. of 321.5-362.6. This retrospective exercise clearly demonstrates that if the cumulative case data used for predictive purpose during an outbreak contains information on the inflection point and about a fortnight after that, the estimate for the total case number can be obtained with excellent accuracy, well before the date of the last reported case. This procedure offers immense possibilities for future public health policy purposes. However, although in our example the estimate for the inflection point became very acceptable rather quickly once the data used for the estimation procedure contains that inflection point (Table 1), the difficult task of how one can correctly determine the true inflection point during a real ongoing epidemic still calls for careful scrutiny and judicious use of the model - as one shall with all mathematical epidemic models.

References:

1. Lipsitch M, Cohen T, Cooper B, Robins JM, Ma S, James L, et al. Transmission dynamics and control of severe acute respiratory syndrome. Science 2003;300:1966–70.

2. Riley S, Fraser C, Donnelly CA, Ghani AC, Abu-Raddad LJ, Hedley AJ, et al. Transmission dynamics of the etiological agent of SARS in Hong Kong: impact of public health interventions. Science 2003;300:1961–6.

3. Dye C, Gay N. Modeling the SARS epidemic. Science 2003; 300: 1884-85 (20 June 2003).

4. Hsieh YH, Chen CWS, & Hsu SB. SARS outbreak, Taiwan 2003. Emerg Infect Dis 2004; To appear.

5. Zhou G, Yan G. Severe acute respiratory syndrome epidemic in Asia. Emerg Infect Dis 2003; Dec 9(12). Available from: URL: http://www.cdc.gov/ncidod/EID/vol9no12/03-0382.htm

6. Ying-Hen Hsieh, Cathy W.S. Chen. Re: Mathematical modeling of SARS: Cautious in all our movements. J Epidem Com Health, 2003; (published online November 18, 2003). Available at http://jech.bmjjournals.com/cgi/eletters/57/6/DC1#66.

7. Razum O, Becher H, Kapaun A, Junghanss T. SARS, lay epidemiology, and fear. Lancet 2003;361:1739–40.

8. World Health Organization. Summary of probable SARS cases with onset of illness from 1 November 2002 to 31 July 2003 (revised 26 September 2003). Available at http://www.who.int/csr/sars/country/table2003_09_23/en/.

9. World Health Organization. Consensus document on the epidemiology of severe acute respiratory syndrome (SARS). October 17, 2003. Available at http://www.who.int/csr/sars/en/WHOconsensus.pdf.

10. Lee ML, Chen CJ, Su IJ, Chen KT, Yeh CC, King CC, et al. Use of quarantine to prevent transmission of severe acute respiratory syndrome--Taiwan, 2003. MMWR Morb. Mortal Wkly Rep. 2003 Jul 25;52(29):680-3.

5.

Control Measures for Severe Acute Respiratory Syndrome (SARS) in Taiwan, Emerging Infectious Diseases, 2003; 9(6): 718-720

hiing-Jer Twu,* Tzay-Jinn Chen,* Chien-Jen Chen,*1 Sonja J. Olsen,† Long-Teng Lee,* Tamara Fisk,†‡ wo-Hsiung Hsu,* Shan-Chwen Chang,*§ Kow-Tong Chen,* I-Hsin Chiang,* Yi-Chun Wu,* Jiunn-Shyan Wu,* and Scott F. Dowell†

As of April 14, 2003, Taiwan had had 23 probable cases of severe acute respiratory syndrome (SARS), 19 of which were imported. Taiwan isolated all 23 patients in negative-pressure rooms; extensive personal protective equipment was used for healthcare workers and visitors. For the first 6 weeks of the SARS outbreak, recognized spread was limited to one healthcare worker and three household contacts.

6.

Antigenicity and Receptor-Binding Ability of Recombinant SARS Coronavirus Spike Protein

Biochemical and Biophysical Research Communications, 2004; 313(4): 938-947

Tin-Yun Ho,^a Shih-Lu Wu,^b Shin-Ei Cheng,^c Yen-Chiao Wei,^c Shan-Ping Huang,^b and Chien-Yun Hsiang^c*

^a Institute of Chinese Medical Science, China Medical University, Taichung, Taiwan

^b Department of Biochemistry, China Medical University, Taichung, Taiwan

^c Department of Microbiology, China Medical University, Taichung, Taiwan

Severe acute respiratory syndrome (SARS) is an emerging infectious disease associated with a novel coronavirus and causing worldwide outbreaks. SARS coronavirus (SARS-CoV) is an enveloped RNA virus, which contains several structural proteins. Among these proteins, spike (S) protein is responsible for binding to specific cellular receptors and is a major antigenic determinant, which induces neutralizing antibody. In order to analyze the antigenicity and receptor-binding ability of SARS-CoV S protein, we expressed the S protein in Escherichia coli using a pET expression vector. After the isopropyl-β-D-thiogalactoside induction, S protein was expressed in the soluble form and was purified by nickel-affinity chromatography to homogeneity. The amount of S protein recovered was 0.2 to 0.3 mg per 100 ml bacterial culture. The S protein was recognized by sera from SARS patients by ELISA and Western blot, indicated that recombinant S protein remained its antigenicity. By biotinylated ELISA and Western blot using biotin- labeled S protein as the probe, we identified 130-kDa and 140-kDa proteins in Vero cells might be the cellular receptors responsible for SARS-CoV infection. Taken together, these results suggested that recombinant S protein exhibited the antigenicity and receptor-binding ability, and it could be a good candidate for further developing SARS vaccine and anti-SARS therapy.

Keywords: SARS; Coronavirus; Spike; Expression; Antigenicity; Receptor binding

7.

Characterization of the SARS Coronavirus Protease Expressed in Escherichia Coli, Biochemical and Biophysical Research Communications (in press)

Cheng-Wen Lin,^a* Chang-Hai Tsai,^b* Fuu-Jen Tsai,^b Chien-Chen Lai,^b Hua-Hao Chiu,^a Kuan-Hsun Lin^a and Pei-Jer Chen^c

^a Department of Medical Laboratory Science and Biotechnology, China Medical University, Taichung 404, Taiwan

^b Department of Medical Genetics and Medical Research, China Medical University, Hospital, Taichung, 404 Taiwan

^cDepartment of Internal Medicine, National Taiwan University College of Medicine,

National Taiwan University Hospital, Taipei 100, Taiwan.

Severe acute respiratory syndrome (SARS) has been globally reported. A novel coronavirus, SARS-coronavirus (SARS-CoV) was identified as the etiological agent of the disease. SARS-CoV 3C-like protease (3CLpro) mediates the proteolytic processing of replicase polypeptides 1a and 1ab into functional proteins, playing an important role in viral replication. In this study, we demonstrated the expression, purification, and functional characterization of the SARS-CoV 3CLpro in E. coli, and identified the cleavage site recognized by the SARS-CoV 3CLpro using the cis-acting proteolytic assays. The identified cleavage site (Thr4426- Val4427- Arg4428- Leu4429- Gln4430- Ala4431- Gly4432- Asn4433- Ala4434- Thr4435) locates within the C-terminal non-structural protein 6 of SARS-CoV, containing a LQA motif recognized by most other coronavirus proteases. Our results will be helpful for developing cheap, rapid, and easy approaches for large-scale screening of the SARS-CoV 3CLpro inhibitors.

8.

Characterization of SARS Coronavirus Genomes in Taiwan: Molecular Epidemiology and Genome Evolution, Proceedings of the National Academy of Sciences of the United States of America (in press)

Shiou-Hwei Yeh,^1,2 Hurng-Yi Wang,³ Ching-Yi Tsai,² Chuan-Liang Kao,⁴ Jyh-Yuan Yang,⁵ Hwan-Wun Liu,⁶ Ih-Jen Su,⁵ Shih-Feng Tsai,¹ Ding-Shinn Chen,^2,7,8 Pei-Jer Chen^2,7,8 and the National Taiwan University SARS Research Team.

¹Division of Molecular and Genomic Medicine, National Health Research Institutes, Taiwan.

²Hepatitis Research Center, National Taiwan University Hospital, Taipei, Taiwan.

³Institute of Molecular Biology, Academia Sinica, Taiwan.

⁴Department of Medical Technology, National Taiwan University, Taipei, Taiwan.

⁵Center for Disease Control, Taipei, Taiwan.

⁶Institute of Preventive Medicine, National Defense Medical College, Taiwan.

⁷Department of Internal Medicine, National Taiwan University Hospital,

⁸Graduate Institute of Clinical Medicine, National Taiwan University College of Medicine, Taipei, Taiwan.

Since early March 2003, the severe acute respiratory syndrome (SARS) coronavirus infection has claimed 346 cases and 37 deaths in Taiwan. The epidemic occurred in two stages. The first stage caused limited familial or hospital infections, and lasted from early March to mid-April. All cases had clear contact histories, primarily from Guangdong or Hong Kong. The second stage resulted in a large outbreak in a municipal hospital, and quickly spread to northern and southern Taiwan from late April to mid-June. During this stage, there were some sporadic cases with untraceable contact histories. To investigate the origin and transmission route of SARS-CoV in Taiwan’s epidemic, we conducted a systematic viral lineage study by sequencing the entire viral genome from ten SARS patients. SARS-CoV viruses isolated from Taiwan were found closely related to those from Guangdong and Hong Kong. In addition, all cases from the second stage belonged to the same lineage following the municipal hospital outbreak, including the patients without an apparent contact history. Analyses of these full-length sequences showed a positive selection occurring during SARS-CoV virus evolution. The mismatch distribution indicated that SARS viral genomes did not reach equilibrium and suggested a recent introduction of the viruses into human populations. The estimated genome mutation rate was approximately 0.1 per genome, demonstrating possibly one of the lowest rates among known RNA viruses.

9.

Microbiologic Characteristics, Serologic Responses, and Clinical Manifestations in Severe Acute Respiratory Syndrome, Taiwan¹, Emerging Infectious Diseases, 2003; 9(9): 1163-1167

Po-Ren Hsueh,* Cheng-Hsiang Hsiao,* Shiou-Hwei Yeh,† Wei-Kung Wang,* Pei-Jer Chen,* Jin-Town Wang,* Shan-Chwen Chang,* Chuan-Liang Kao,* Pan-Chyr Yang,* and The SARS Research Group of National Taiwan University College of Medicine and National Taiwan University Hospital²

*National Taiwan University Hospital, National Taiwan University College of Medicine, Taipei, Taiwan

†National Health Research Institute, Taipei, Taiwan

¹The first and the second author contributed equally to this paper.

²The SARS Research Group of National Taiwan University College of Medicine and National Taiwan University Hospital includes the following: Ding-Shinn Chen, Yuan-Teh Lee, Che-Ming Teng, Pan- Chyr Yang, Hong-Nerng Ho, Pei-Jer Chen, Ming-Fu Chang, Jin- Town Wang, Shan-Chwen Chang, Chuan-Liang Kao, Wei-Kung Wang, Cheng-Hsiang Hsiao, and Po-Ren Hsueh.

The genome of one Taiwanese severe acute respiratory syndrome-associated coronavirus (SARS-CoV) strain (TW1) was 29,729 nt in length. Viral RNA may persist for some time in patients who seroconvert, and some patients may lack an antibody response (immunoglobulin G) to SARS-CoV >21 days after illness onset. An upsurge of antibody response was associated with the aggravation of respiratory failure.

10.

Detection of Large Amount of SARS-Associated Coronavirus in Saliva and Throat Wash: Implications for Transmission and Early Diagnosis, Journal of Infectious Diseases (in press)

Wei-Kung Wang,^1,2 Shey-Ying Chen,^3a I-Jung Liu,^1a Yee-Chun Chen,² Jann-Tay Wang,² Wang-Hwei Sheng,² Chi-Tai Fang,² Hui-Ling Chen,¹ Chao-Fu Yang,¹ Pei-Jer Chen,^2,4 Shiou-Hwei Yeh,⁵ Chuan-Liang Kao,⁶ Li-Min Huang,⁷ Po-Ren Hsueh,² Chien-Ching Hung,² Szu-Min Hsieh,² Chan-Ping Su,³ Wen-Chu Chiang,³ Jyh-Yuan Yang,⁸ Jih-Hui Lin,⁸ Szu-Chia Hsieh,¹ Hsien-Ping Hu,¹ Yu-Ping Chiang,¹ Jin-Town Wang,¹ Pan-Chyr Yang,² Shan-Chwen Chang,² and members of the SARS Research Group of the NTUCM/NTUH

¹Institute of Microbiology, ⁴Clinical Medicine, and ⁶Medical Technology, College of Medicine, National Taiwan University, Taipei, Taiwan

²Department of Internal Medicine, ³Emergency Medicine, and ⁷Pediatrics, National Taiwan University Hospital, Taipei, Taiwan

⁵National Health Research Institute, Taipei, Taiwan

⁸Center for Disease Control, Department of Health, Taipei, Taiwan

The severe acute respiratory syndrome (SARS)-associated coronavirus, SARS-CoV, is known to be transmitted primarily through contact of and dispersal of droplets.  Little is known about the load of SARS-CoV in oral droplets.  In this study, we examined oral specimens including saliva and throat wash, and reported that large amount of SARS-CoV RNA were found in both saliva (7.08 X 10³ to 6.38 X 10⁸ copies /ml) and throat wash (9.58 X 10² to 5.93 X 10⁶ copies /ml) from all 14 consecutive probable SARS cases studied, providing a direct evidence of transmission through oral droplets.  Immunofluorescence study revealed replication of SARS-CoV in the cells derived from throat wash, demonstrating the first convenient antigen detection assay for SARS-CoV.  This finding together with the high detection rate at a median of 4.5 days after disease onset and before the development of lung lesion in 4 cases suggest that saliva and throat wash be included in the current guidelines of sample collection for SARS diagnosis.

11.

Generation and Characterization of DNA Vaccines Targeting the Nucleocapsid Protein of Severe Acute Respiratory Syndrome Coronavirus, Journal of Virology 2004; 78(9): 4638-4645

Tae Woo Kim,¹ Jin Hyup Lee,¹ Chien-Fu Hung,¹ Shiwen Peng,¹ Richard Roden,^1,2 Mei-Cheng Wang,³ Raphael Viscidi,⁴ Ya-Chea Tsai,¹ Liangmei He,¹ Pei-Jer Chen,^5,6 David A. K. Boyd,¹ and T.-C. Wu^1,2,7,8*

Departments of Pathology,¹ Pediatrics,⁴ Oncology,⁷ Biostatistics,³ Obstetrics and Gynecology,² Molecular Microbiology and Immunology, The Johns Hopkins Medical Institutions, Baltimore, Maryland 21205,⁸ Graduate Institute of Clinical Medicine,⁵ Hepatitis Research Center, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan⁶

Severe acute respiratory syndrome (SARS) is a serious threat to public health and the economy on a global scale. The SARS coronavirus (SARS-CoV) has been identified as the etiological agent for SARS. Thus, vaccination against SARS-CoV may represent an effective approach to controlling SARS. DNA vaccines are an attractive approach for SARS vaccine development, as they offer many advantages over conventional vaccines, including stability, simplicity, and safety. Our investigators have previously shown that DNA vaccination with antigen linked to calreticulin (CRT) dramatically enhances major histocompatibility complex class I presentation of linked antigen to CD8⁺ T cells. In this study, we have employed this CRT-based enhancement strategy to create effective DNA vaccines using SARS-CoV nucleocapsid (N) protein as a target antigen. Vaccination with naked CRT/N DNA generated the most potent N-specific humoral and T-cell-mediated immune responses in vaccinated C57BL/6 mice among all of the DNA constructs tested. Furthermore, mice vaccinated with CRT/N DNA were capable of significantly reducing the titer of challenging vaccinia virus expressing the N protein of the SARS virus. These results show that a DNA vaccine encoding CRT linked to a SARS-CoV antigen is capable of generating strong N-specific humoral and cellular immunity and may potentially be useful for control of infection with SARS-CoV.

12.

Patient data, early SARS epidemic, Taiwan, Emerging Infectious Diseases 2004; 10(3): 489-493

Hsueh PR, Chen PJ, Hsiao CH, Yeh SH, Cheng WC, Wang JL, Chiang BL, Chang SC, Chang FY, Wong WW, Kao CL, Yang PC, SARS Research Group of National Taiwan University College of Medicine and National Taiwan University Hospital

National Taiwan University College of Medicine, No. 7 Chung-Shan South Road, Taipei, Taiwan.

Of the first 10 patients in the epidemic of severe acute respiratory syndrome (SARS) in Taiwan, 4 were closely associated with a SARS patient in an airplane. Loose stools or diarrhea, hemophagocytosis syndrome, and high serum levels of interleukin (IL)-6, IL-8, and tumor necrosis factor-a associated with lung lesions were found in all 10 patients.

13.

Assembly of Human Severe Acute Respiratory Syndrome (SARS) Coronavirus-like Particles, Biochemical and Biophysical Research Communications (accepted)

Yu Ho, Pi-Hsiu Lin, Catherine Y. Y. Liu, Su-Ping Lee, and Yu-Chan Chao*

Institute of Molecular Biology, Academia Sinica, Nankang, Taipei 115, Taiwan, ROC.

Viral particles of human severe acute respiratory syndrome coronavirus (SARS-CoV) consist of three virion structural proteins, including spike protein, membrane protein, and envelope protein. In this report, virus-like particles were assembled in insect cells by the co-infection with recombinant baculoviruses, which separately expressing one of these three virion proteins. We found that the membrane and envelope proteins are sufficient for the efficient formation of virus-like particles and could be visualized by electron microscopy. Sucrose gradient purification ollowed by Western analysis and immunogold labeling showed that the spike protein could be incorporated into the virus like particle also. The construction of engineered virus-like particles bear resemblance to the authentic one is an important step towarding the development of an effective vaccine against infection of SARS CoV.

14.  

SARS Outbreak in Taiwan (Reply to Hsieh et al), Emerging Infectious Diseases (in press)

Po-Ren Hsueh* and Pan-Chyr Yang

*^,ϯNational Taiwan University Hospital, National Taiwan University College of Medicine, Taipei, Taiwan.

Directors of Case classification* and Clinical Management^ϯ of SARS, the SARS Prevention and Extrication Committee, Department of Health, Executive Yuan, Taiwan, Republic of China.

In Reply to Hsieh et al: The article by Hsieh et al. analyzed the daily case-report data for severe acute respiratory syndrome (SARS) from May 5 to June 4 2003, which were posted on the website of the Center for Disease Control of Taiwan, to show how this disease had spread so rapidly in the 2003 outbreak (1). They suggested that infection from hospitalized patients with suspected cases of SARS which had not yet reclassified as probable cases was a major factor in the rapid spread of the disease in hospitals. Slow reclassification and delayed placement of patients with initially suspected cases in negative-pressure isolation rooms contributed to the high percentage (73%) of nosocomial infection in Taiwan (1).

During the study period (stage II) of the outbreak, there were three teams responsible for the classification of SARS cases (2). The team members included infectious disease specialists, chest physicians, and epidemiologists, recruited from major teaching hospitals in the northern, middle, and southern parts of Taiwan, and were organized by the Taiwan CDC and the National Health Insurance Bureau. They met daily and reviewed the clinical data, travel and contact history, and chest radiography of the reported cases obtained (via email or fax) from attending physicians caring for the patients. The same protocol (Table) was used by all members to classify the cases as suspected or probable. All hospitals that cared for the suspected SARS patients either had their own committee to classify patients according to World Health Organization (WHO) guidelines or followed the above protocol for classification or reclassification of reported cases by the team members (3).

Although official reclassification might well have taken the twelve and a half days suggested by Hsieh et al, the conclusion that inadequate isolation of patients during this period led to significant nosocomial transmission cannot be based upon the data available to these authors. From the first day that suspected cases were reported to the Taiwan CDC, patients were placed in negative-pressure isolation rooms whenever available. While suspected cases may have been less likely than probable cases to be placed in negative-pressure isolation rooms where these were in short supply, all other available isolation precautions were used to care for suspect case patients while they were undergoing reclassification. The notion that significant transmission occurred despite these isolation precautions is not consistent with the literature suggesting the central role of gloves, gowns, and surgical masks in preventing transmission (4). Thus the process of reclassification was not associated with the timing of isolation measures shown to have the greatest impact in preventing transmission.

The high proportion of patients with nosocomial SARS infection in Taiwan is consistent with the observations of Lingappa et al (5) and others who have noted that the hospital setting was the primary amplifier of SARS transmission with significant community transmission occurring in only the largest of outbreaks. The high proportion of nosocomial cases suggests that containment measures instituted in Taiwan were ultimately successful in preventing a much larger outbreak. Multiple factors were associated with the nosocomial outbreaks in Taiwan including inadequate infection control infrastructure and triage screening leading to delayed detection of several highly contagious index cases.

References:

1.          Hsieh YH, Chen CWS, Hsu SB. SARS outbreak, Taiwan, 2003. Emerg Infect Dis 2004;10:201-6.

2.          Center for Disease Control, Department of Health, Executive Yuan, Taiwan: Memoir of severe acute respiratory syndrome control in Taiwan. 2003. Available from: URL: http://www.cdc.gov.tw

3.          World Health Organization. Case definition for surveillance of severe acute respiratory syndrome (SARS). Geneva: 1 May 2003. Available from: URL: http://www.who.int/csr/sars/casedefinition/en.

4.          Loeb M, McGeer A, Henry B, Ofner M, Rose D, Hlywka T, et al. SARS among critical care nurses, Toronto. Emerg Infect Dis 2004;10:251-5.

5.          Lingappa JR, McDonald LC, Simone P, Parashar UD. Wresting SARS from uncertainty. Emerg Infect Dis 2004;10:167-70.