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2.
Transbound Emerg Dis ; 2020 May 26.
Artigo em Inglês | MEDLINE | ID: mdl-32452648

RESUMO

BACKGROUNDS: The novel coronavirus disease (COVID-19) poses serious threat to global public health and economics. Serial interval (SI), time between the symptom onsets of a primary case and a second case, is a key epidemiological parameter. We estimated SI of COVID-19 in Shenzhen, China based on 27 records of transmission chains. METHODS: We adopted three parametric models: Weibull, Lognormal and Gamma distributions and an interval censored likelihood framework. The three models were compared using the corrected Akaike information criterion (AICc). We also fitted the epidemic curve of COVID-19 to the exponential growth to estimate the reproduction number. FINDINGS: Using a Weibull distribution, we estimated mean SI at 5.9 days (95%CI: 3.9-9.6) and a standard deviation (SD) at 4.8 days (95%CI: 3.1-10.1). Using a logistic growth model, we estimated the basic reproduction number in Shenzhen at 2.6 (95%CI: 2.4-2.8). CONCLUSION: The SI of COVID-19 is relative shorter than that of SARS and MERS, other two beta coronavirus diseases, which suggests the iteration of the transmission was rapid. It is crucial to isolate close contacts promptly to control the spread of COVID-19 effectively.

3.
Int J Infect Dis ; 96: 284-287, 2020 May 08.
Artigo em Inglês | MEDLINE | ID: mdl-32413609

RESUMO

BACKGROUNDS: The emerging virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), caused a large outbreak of coronavirus disease, COVID-19, in Wuhan, China, since December 2019. COVID-19 soon spread to other regions of China and overseas. In Hong Kong, local mitigation measures were implemented since the first imported case was confirmed on January 23, 2020. Here we evaluated the temporal variation of detection delay from symptoms onset to laboratory confirmation of SARS-CoV-2 in Hong Kong. METHODS: A regression model is adopted to quantify the association between the SARS-CoV-2 detection delay and calendar time. The association is tested and further validated by a Cox proportional hazard model. FINDINGS: The estimated median detection delay was 9.5 days (95%CI: 6.5-11.5) in the second half of January, reduced to 6.0 days (95%CI: 5.5-9.5) in the first half of February 2020. We estimate that SARS-CoV-2 detection efficiency improved at a daily rate of 5.40% (95%CI: 2.54-8.33) in Hong Kong. CONCLUSIONS: The detection efficiency of SARS-CoV-2 was likely being improved substantially in Hong Kong since the first imported case was detected. Sustaining enforcement in timely detection and other effective control measures are recommended to prevent the SARS-CoV-2 infection.

4.
Int J Infect Dis ; 95: 308-310, 2020 Apr 22.
Artigo em Inglês | MEDLINE | ID: mdl-32334115

RESUMO

The novel coronavirus disease 2019 (COVID-19) outbreak has caused 6088 cases and 41 deaths in Republic of Korea, and 3144 cases and 107 death in Italy by 5 March 2020, respectively. We modelled the transmission process in the Republic of Korea and Italy with a stochastic model, and estimated the basic reproduction number R0 as 2.6 (95% CI: 2.3-2.9) or 3.2 (95% CI: 2.9-3.5) in the Republic of Korea, under the assumption that the exponential growth starting on 31 January or 5 February 2020, and 2.6 (95% CI: 2.3-2.9) or 3.3 (95% CI: 3.0-3.6) in Italy, under the assumption that the exponential growth starting on 5 February or 10 February 2020, respectively.

5.
Int J Infect Dis ; 94: 145-147, 2020 May.
Artigo em Inglês | MEDLINE | ID: mdl-32315808

RESUMO

Asymptomatic transmission of the coronavirus disease 2019 is an important topic. A recent study in China showed that transmissibility of the asymptomatic cases is comparable to that of symptomatic cases. Here, we discuss that the conclusion may depend on how we interpret the data. To the best of our knowledge, this is the first time the relative transmissibility of asymptomatic COVID-19 infections is quantified.


Assuntos
Infecções Assintomáticas , Betacoronavirus , Infecções por Coronavirus/transmissão , Pneumonia Viral/transmissão , China , Humanos , Pandemias
7.
PLoS Negl Trop Dis ; 14(4): e0007502, 2020 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-32348302

RESUMO

BACKGROUND: Between January 2015 and August 2016, two epidemic waves of Zika virus (ZIKV) disease swept the Northeastern (NE) region of Brazil. As a result, two waves of Guillain-Barré Syndrome (GBS) were observed concurrently. The mandatory reporting of ZIKV disease began region-wide in February 2016, and it is believed that ZIKV cases were significantly under-reported before that. The changing reporting rate has made it difficult to estimate the ZIKV infection attack rate, and studies in the literature vary widely from 17% to > 50%. The same applies to other key epidemiological parameters. In contrast, the diagnosis and reporting of GBS cases were reasonably reliable given the severity and easy recognition of the disease symptoms. In this paper, we aim to estimate the real number of ZIKV cases (i.e., the infection attack rate) and their dynamics in time, by scaling up from GBS surveillance data in NE Brazil. METHODOLOGY: A mathematical compartmental model is constructed that makes it possible to infer the true epidemic dynamics of ZIKV cases based on surveillance data of excess GBS cases. The model includes the possibility that asymptomatic ZIKV cases are infectious. The model is fitted to the GBS surveillance data and the key epidemiological parameters are inferred by using a plug-and-play likelihood-based estimation. We make use of regional weather data to determine possible climate-driven impacts on the reproductive number [Formula: see text], and to infer the true ZIKV epidemic dynamics. FINDINGS AND CONCLUSIONS: The GBS surveillance data can be used to study ZIKV epidemics and may be appropriate when ZIKV reporting rates are not well understood. The overall infection attack rate (IAR) of ZIKV is estimated to be 24.1% (95% confidence interval: 17.1%-29.3%) of the population. By examining various asymptomatic scenarios, the IAR is likely to be lower than 33% over the two ZIKV waves. The risk rate from symptomatic ZIKV infection to develop GBS was estimated as ρ = 0.0061% (95% CI: 0.0050%-0.0086%) which is significantly less than current estimates. We found a positive association between local temperature and the basic reproduction number, [Formula: see text]. Our analysis revealed that asymptomatic infections affect the estimation of ZIKV epidemics and need to also be carefully considered in related modelling studies. According to the estimated effective reproduction number and population wide susceptibility, we comment that a ZIKV outbreak would be unlikely in NE Brazil in the near future.

8.
Int J Infect Dis ; 94: 29-31, 2020 May.
Artigo em Inglês | MEDLINE | ID: mdl-32171951

RESUMO

As of March 1, 2020, Iran had reported 987 novel coronavirus disease (COVID-19) cases, including 54 associated deaths. At least six neighboring countries (Bahrain, Iraq, Kuwait, Oman, Afghanistan, and Pakistan) had reported imported COVID-19 cases from Iran. In this study, air travel data and the numbers of cases from Iran imported into other Middle Eastern countries were used to estimate the number of COVID-19 cases in Iran. It was estimated that the total number of cases in Iran was 16 533 (95% confidence interval: 5925-35 538) by February 25, 2020, before the UAE and other Gulf Cooperation Council countries suspended inbound and outbound flights from Iran.


Assuntos
Betacoronavirus/fisiologia , Infecções por Coronavirus/transmissão , Pneumonia Viral/transmissão , Doença Relacionada a Viagens , Viagem Aérea , Humanos , Irã (Geográfico) , Pandemias
11.
Int J Infect Dis ; 93: 211-216, 2020 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-32145465

RESUMO

The ongoing coronavirus disease 2019 (COVID-19) outbreak, emerged in Wuhan, China in the end of 2019, has claimed more than 2600 lives as of 24 February 2020 and posed a huge threat to global public health. The Chinese government has implemented control measures including setting up special hospitals and travel restriction to mitigate the spread. We propose conceptual models for the COVID-19 outbreak in Wuhan with the consideration of individual behavioural reaction and governmental actions, e.g., holiday extension, travel restriction, hospitalisation and quarantine. We employe the estimates of these two key components from the 1918 influenza pandemic in London, United Kingdom, incorporated zoonotic introductions and the emigration, and then compute future trends and the reporting ratio. The model is concise in structure, and it successfully captures the course of the COVID-19 outbreak, and thus sheds light on understanding the trends of the outbreak.


Assuntos
Infecções por Coronavirus/epidemiologia , Surtos de Doenças , Modelos Biológicos , Pneumonia Viral/epidemiologia , Saúde Pública/legislação & jurisprudência , Betacoronavirus , China/epidemiologia , Governo , Regulamentação Governamental , Humanos , Influenza Pandêmica, 1918-1919/estatística & dados numéricos , Pandemias , Quarentena , Viagem/legislação & jurisprudência , Reino Unido/epidemiologia
13.
Int J Infect Dis ; 92: 214-217, 2020 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-32007643

RESUMO

BACKGROUNDS: An ongoing outbreak of a novel coronavirus (2019-nCoV) pneumonia hit a major city in China, Wuhan, December 2019 and subsequently reached other provinces/regions of China and other countries. We present estimates of the basic reproduction number, R0, of 2019-nCoV in the early phase of the outbreak. METHODS: Accounting for the impact of the variations in disease reporting rate, we modelled the epidemic curve of 2019-nCoV cases time series, in mainland China from January 10 to January 24, 2020, through the exponential growth. With the estimated intrinsic growth rate (γ), we estimated R0 by using the serial intervals (SI) of two other well-known coronavirus diseases, MERS and SARS, as approximations for the true unknown SI. FINDINGS: The early outbreak data largely follows the exponential growth. We estimated that the mean R0 ranges from 2.24 (95%CI: 1.96-2.55) to 3.58 (95%CI: 2.89-4.39) associated with 8-fold to 2-fold increase in the reporting rate. We demonstrated that changes in reporting rate substantially affect estimates of R0. CONCLUSION: The mean estimate of R0 for the 2019-nCoV ranges from 2.24 to 3.58, and is significantly larger than 1. Our findings indicate the potential of 2019-nCoV to cause outbreaks.


Assuntos
Número Básico de Reprodução , Betacoronavirus/fisiologia , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/transmissão , Pneumonia Viral/epidemiologia , Pneumonia Viral/transmissão , China/epidemiologia , Infecções por Coronavirus/diagnóstico , Epidemias , Humanos , Coronavírus da Síndrome Respiratória do Oriente Médio/fisiologia , Pandemias , Pneumonia Viral/diagnóstico , Vírus da SARS/fisiologia , Organização Mundial da Saúde
14.
Infect Dis (Lond) ; 52(4): 284-290, 2020 04.
Artigo em Inglês | MEDLINE | ID: mdl-32013645

RESUMO

Background: Globally, a resurgence of measles during the last decade may be attributed to many factors. An unexpected measles outbreak occurred in Hong Kong, and infected 29 airport staff between March and April 2019. The authority updated public on new cases daily, a public enquiry telephone/online platform was set up on March 23, and an emergent vaccination programme was launched targeting unvaccinated airport staff. We aimed to study this measles outbreak and its related factors.Methods: We quantified the transmissibility of the outbreak by the time-varying effective reproduction number, Reff(t), and inferred the time-varying basic reproduction number, R0(t). We examined the statistical associations between local public awareness or reporting delay and the R0(t).Results: Our estimated average R0 is 10.7 with 95% CI of 6.0-29.2. We found that R0(t) was negatively associated with the level of public awareness and the level of promptness of situation updates on new cases.Conclusion: Public awareness via situation updates helped to control the outbreak. The medical effects of the vaccination programme was not soon enough to cause the immediate shutting down of the outbreak, but it boosted herd immunity to prevent future airport outbreaks in the next few years.

17.
J Theor Biol ; 493: 110209, 2020 May 21.
Artigo em Inglês | MEDLINE | ID: mdl-32097608

RESUMO

Lassa fever, also known as Lassa hemorrhagic fever, is a virus that has generated recurrent outbreaks in West Africa. We use mechanistic modelling to study the Lassa fever epidemics in Nigeria from 2016-19. Our model describes the interaction between human and rodent populations with the consideration of quarantine, isolation and hospitalization processes. Our model supports the phenomenon of forward bifurcation where the stability between disease-free equilibrium and endemic equilibrium exchanges. Moreover, our model captures well the incidence curves from surveillance data. In particular, our model is able to reconstruct the periodic rodent and human forces of infection. Furthermore, we suggest that the three major epidemics from 2016-19 can be modelled by properly characterizing the rodent (or human) force of infection while the estimated human force of infection also present similar patterns across outbreaks. Our results suggest that the initial susceptibility likely increased across the three outbreaks from 2016-19. Our results highlight the similarity of the transmission dynamics driving three major Lassa fever outbreaks in the endemic areas.

18.
Epidemiol Infect ; 148: e4, 2020 Jan 10.
Artigo em Inglês | MEDLINE | ID: mdl-31918780

RESUMO

Lassa fever (LF) is increasingly recognised as an important rodent-borne viral haemorrhagic fever presenting a severe public health threat to sub-Saharan West Africa. In 2017-18, LF caused an unprecedented epidemic in Nigeria and the situation was worsening in 2018-19. This work aims to study the epidemiological features of epidemics in different Nigerian regions and quantify the association between reproduction number (R) and state rainfall. We quantify the infectivity of LF by the reproduction numbers estimated from four different growth models: the Richards, three-parameter logistic, Gompertz and Weibull growth models. LF surveillance data are used to fit the growth models and estimate the Rs and epidemic turning points (τ) in different regions at different time periods. Cochran's Q test is further applied to test the spatial heterogeneity of the LF epidemics. A linear random-effect regression model is adopted to quantify the association between R and state rainfall with various lag terms. Our estimated Rs for 2017-18 (1.33 with 95% CI 1.29-1.37) was significantly higher than those for 2016-17 (1.23 with 95% CI: (1.22, 1.24)) and 2018-19 (ranged from 1.08 to 1.36). We report spatial heterogeneity in the Rs for epidemics in different Nigerian regions. We find that a one-unit (mm) increase in average monthly rainfall over the past 7 months could cause a 0.62% (95% CI 0.20%-1.05%)) rise in R. There is significant spatial heterogeneity in the LF epidemics in different Nigerian regions. We report clear evidence of rainfall impacts on LF epidemics in Nigeria and quantify the impact.

19.
Trans R Soc Trop Med Hyg ; 114(1): 62-71, 2020 Jan 06.
Artigo em Inglês | MEDLINE | ID: mdl-31638154

RESUMO

BACKGROUND: Dengue remains a severe threat to public health in tropical and subtropical regions. In China, over 85% of domestic dengue cases are in the Guangdong province and there were 53 139 reported cases during 2008-2018. In Guangdong, the 2014 dengue outbreak was the largest in the last 20 y and it was probably triggered by a new strain imported from other regions. METHODS: We studied the long-term patterns of dengue infectivity in Guangdong from 2008-2018 and compared the infectivity estimates across different periods. RESULTS: We found that the annual epidemics approximately followed exponential growth during 2011-2014. The transmission rates were at a low level during 2008-2012, significantly increased 1.43-fold [1.22, 1.69] during 2013-2014 and then decreased back to a low level after 2015. By using the mosquito index and the likelihood-inference approach, we found that the new strain most likely invaded Guangdong in April 2014. CONCLUSIONS: The long-term changing dynamics of dengue infectivity are associated with the new dengue virus strain invasion and public health control programmes. The increase in infectiousness indicates the potential for dengue to go from being imported to becoming an endemic in Guangdong, China.

20.
J Theor Biol ; 486: 110070, 2020 Feb 07.
Artigo em Inglês | MEDLINE | ID: mdl-31697940

RESUMO

Multiple-wave outbreaks have been documented for influenza pandemics particularly in the temperate zone, and occasionally for seasonal influenza epidemics in the tropical zone. The mechanisms shaping multiple-wave influenza outbreaks are diverse but are yet to be summarized in a systematic fashion. For this purpose, we described 12 distinct mechanistic models, among which five models were proposed for the first time, that support two waves of infection in a single influenza season, and classified them into five categories according to heterogeneities in host, pathogen, space, time and their combinations, respectively. To quantify the number of infection waves, we proposed three metrics that provide robust and intuitive results for real epidemics. Further, we performed sensitivity analyses on key parameters in each model and found that reducing the basic reproduction number or the transmission rate, limiting the addition of susceptible people who are to get the primary infection to infected areas, and limiting the probability of replenishment of people who are to be reinfected in the short term, could decrease the number of infection waves and clinical attack rate. Finally, we introduced a modelling framework to infer the mechanisms driving two-wave outbreaks. A better understanding of two-wave mechanisms could guide public health authorities to develop and implement preparedness plans and deploy control strategies.

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