Inferring high-resolution human mixing patterns for disease modeling

Dina Mistry, Maria Litvinova, Ana Pastore y Piontti, Matteo Chinazzi, Laura Fumanelli, Marcelo F. C. Gomes, Syed A. Haque, Quan-Hui Liu, Kunpeng Mu, Xinyue Xiong, M. Elizabeth Halloran, Ira M. Longini Jr., Stefano Merler, Marco Ajelli, Alessandro Vespignani

Nature Communications

January 12, 2021

ABSTRACT

Mathematical and computational modeling approaches are increasingly used as quantitative tools in the analysis and forecasting of infectious disease epidemics. The growing need for realism in addressing complex public health questions is, however, calling for accurate models of the human contact patterns that govern the disease transmission processes. Here we present a data-driven approach to generate effective population-level contact matrices by using highly detailed macro (census) and micro (survey) data on key socio-demographic features. We produce age-stratified contact matrices for 35 countries, including 277 sub-national administrative regions of 8 of those countries, covering approximately 3.5 billion people and reflecting the high degree of cultural and societal diversity of the focus countries. We use the derived contact matrices to model the spread of airborne infectious diseases and show that sub-national heterogeneities in human mixing patterns have a marked impact on epidemic indicators such as the reproduction number and overall attack rate of epidemics of the same etiology. The contact patterns derived here are made publicly available as a modeling tool to study the impact of socio-economic differences and demographic heterogeneities across populations on the epidemiology of infectious diseases.

Cost-effectiveness of live-attenuated influenza vaccination among school-age children

Natasha S.Wenzel, Katherine E.Atkins, Edwin van Leeuwen, M. Elizabeth Halloran, Marc Baguelin

Vaccine

January 8, 2021

ABSTRACT

The current pediatric vaccination program in England and Wales administers Live-Attenuated Influenza Vaccine (LAIV) to children ages 2–16 years old. Annual administration of LAIV to this age group is costly and poses substantial logistical issues. This study aims to evaluate the cost-effectiveness of prioritizing vaccination to age groups within the 2–16 year old age range to mitigate the operational and resource challenges of the current strategy. We performed economic evaluations comparing the influenza vaccination program from 1995–2013 to seven alternative strategies targeted at low risk individuals along the school age divisions Preschool (2–4 years old), Primary school (5–11 years old), and Secondary school (12–16 years old). These extensions are evaluated incrementally on the status quo scenario (vaccinating subgroups at high risk of influenza-related complications and individuals 65+ years old). Impact of vaccination was assessed using a transmission model from a previously published study and updated with new data. At all levels of coverage, all strategies had a 100% probability of being cost-effective at the current National Health Service threshold, £20,000/QALY gained. The incremental analysis demonstrated vaccinating Primary School children was the most cost-efficient strategy compared incrementally against others with an Incremental Cost-Effectiveness Ratio of £639 spent per QALY gained (Net Benefit: 404 M£ [155, 795]). When coverage was varied between 30%, 55%, and 70% strategies which included Primary school children had a higher probability of being cost-effective at lower willingness-to-pay levels. Although children were the vaccine target the majority of QALY gains occurred in the 25–44 years old and 65+ age groups. Influenza strain A/H3N2 incurred the greatest costs and QALYs lost regardless of which strategy was used. Improvement could be made to the current LAIV pediatric vaccination strategy by eliminating vaccination of 2–4 year olds and focusing on school-based delivery to Primary and Secondary school children in tandem.

Household Transmission of SARS-CoV-2: A Systematic Review and Meta-analysis

Zachary J. Madewell, Yang Yang, Ira M. Longini Jr, M. Elizabeth Halloran, Natalie E. Dean

JAMA Network Open

December 14, 2020

ABSTRACT

Objectives :To examine evidence for household transmission of SARS-CoV-2, disaggregated by several covariates, and to compare it with other coronaviruses.

Data Source: PubMed, searched through October 19, 2020. Search terms included SARS-CoV-2 or COVID-19 with secondary attack rate, household, close contacts, contact transmission, contact attack rate, or family transmission.

Study Selection: All articles with original data for estimating household secondary attack rate were included. Case reports focusing on individual households and studies of close contacts that did not report secondary attack rates for household members were excluded.

Data Extraction and Synthesis: Meta-analyses were done using a restricted maximum-likelihood estimator model to yield a point estimate and 95% CI for secondary attack rate for each subgroup analyzed, with a random effect for each study. To make comparisons across exposure types, study was treated as a random effect, and exposure type was a fixed moderator. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline was followed.

Main Outcomes and Measures: Secondary attack rate for SARS-CoV-2, disaggregated by covariates (ie, household or family contact, index case symptom status, adult or child contacts, contact sex, relationship to index case, adult or child index cases, index case sex, number of contacts in household) and for other coronaviruses.

Results: A total of 54 relevant studies with 77 758 participants reporting household secondary transmission were identified. Estimated household secondary attack rate was 16.6% (95% CI, 14.0%-19.3%), higher than secondary attack rates for SARS-CoV (7.5%; 95% CI, 4.8%-10.7%) and MERS-CoV (4.7%; 95% CI, 0.9%-10.7%). Household secondary attack rates were increased from symptomatic index cases (18.0%; 95% CI, 14.2%-22.1%) than from asymptomatic index cases (0.7%; 95% CI, 0%-4.9%), to adult contacts (28.3%; 95% CI, 20.2%-37.1%) than to child contacts (16.8%; 95% CI, 12.3%-21.7%), to spouses (37.8%; 95% CI, 25.8%-50.5%) than to other family contacts (17.8%; 95% CI, 11.7%-24.8%), and in households with 1 contact (41.5%; 95% CI, 31.7%-51.7%) than in households with 3 or more contacts (22.8%; 95% CI, 13.6%-33.5%).

Conclusions and Relevance :The findings of this study suggest that given that individuals with suspected or confirmed infections are being referred to isolate at home, households will continue to be a significant venue for transmission of SARS-CoV-2.

Estimates of inactivated influenza vaccine effectiveness among children in Senegal: results from two consecutive cluster-randomized controlled trials in 2010 and 2011

Mbayame Nd Niang, Jonathan D Sugimoto, Aldiouma Diallo, Bou Diarra, Justin R Ortiz, Kristen D C Lewis, Kathryn E Lafond, M Elizabeth Halloran, Marc-Alain Widdowson, Kathleen M Neuzil, John C Victor

Clinical Infectious Diseases

November 9, 2020

ABSTRACT

Background

We report results of Years 2 and 3 of consecutive cluster-randomized controlled trials of trivalent inactivated influenza vaccine (IIV3) in Senegal.

Methods

We cluster-randomized (1:1) 20 villages to annual vaccination with IIV3 or inactivated poliovirus vaccine (IPV) of age-eligible residents (6 months – 10 years). The primary outcome was total vaccine effectiveness against laboratory-confirmed influenza illness (LCI) among age-eligible children (modified-intention-to-treat population [mITT]). Secondary outcomes were indirect (herd protection) and population (overall community) vaccine effectiveness.

Results

We vaccinated 74% of 12,408 age-eligible children in Year 2 (June 2010-April 11) and 74% of 11,988 age-eligible children in Year 3 (April 2011-December 2011) with study vaccines. Annual cumulative incidence of LCI was 4.7 (Year 2) and 4.2 (Year 3) per 100 mITT child vaccinees of IPV villages. In Year 2, IIV3 matched circulating influenza strains. The total effectiveness was 52.8% (95% CI: 32.3%–67.0%), and the population effectiveness was 36.0% (95% CI: 10.2%–54.4%) against LCI caused by any influenza strain. The indirect effectiveness against LCI by A/H3N2 was 56.4% (95% CI: 39.0%–68.9%). In Year 3, 74% of influenza detections were vaccine-mismatched to circulating B/Yamagata and 24% were vaccine-matched to circulating A/H3N2. The Year 3 total effectiveness against LCI was -14.5% (95% CI: -81.2%–27.6%). Vaccine effectiveness varied by type/subtype of influenza in both years.

Conclusion

IIV3 was variably effective against influenza illness in Senegalese children, with total and indirect vaccine effectiveness present during the year when all circulating strains matched the IIV3 formulation.

Ensemble forecast modeling for the design of COVID-19 vaccine efficacy trials

Natalie E Dean, Ana Pastore Y Piontti, Zachary J Madewell, Derek A T Cummings, Matthew D T Hitchings, Keya Joshi, Rebecca Kahn, Alessandro Vespignani, M Elizabeth Halloran, Ira M Longini Jr

Vaccine

October 27, 2020

ABSTRACT

To rapidly evaluate the safety and efficacy of COVID-19 vaccine candidates, prioritizing vaccine trial sites in areas with high expected disease incidence can speed endpoint accrual and shorten trial duration. Mathematical and statistical forecast models can inform the process of site selection, integrating available data sources and facilitating comparisons across locations. We recommend the use of ensemble forecast modeling – combining projections from independent modeling groups – to guide investigators identifying suitable sites for COVID-19 vaccine efficacy trials. We describe an appropriate structure for this process, including minimum requirements, suggested output, and a user-friendly tool for displaying results. Importantly, we advise that this process be repeated regularly throughout the trial, to inform decisions about enrolling new participants at existing sites with waning incidence versus adding entirely new sites. These types of data-driven models can support the implementation of flexible efficacy trials tailored to the outbreak setting.

Zika virus infection enhances future risk of severe dengue disease

Leah C. Katzelnick, César Narvaez, Sonia Arguello, Brenda Lopez Mercado, Damaris Collado, Oscarlett Ampie, Douglas Elizondo, Tatiana Miranda, Fausto Bustos Carillo, Juan Carlos Mercado, Krista Latta, Amy Schiller, Bruno Segovia-Chumbez, Sergio Ojeda, Nery Sanchez, Miguel Plazaola, Josefina Coloma, M. Elizabeth Halloran, Lakshmanane Premkumar, Aubree Gordon, Federico Narvaez, Aravinda M. de Silva, Guillermina Kuan, Angel Balmaseda, Eva Harris

Science

August 28, 2020

ABSTRACT

The Zika pandemic sparked intense interest in whether immune interactions among dengue virus serotypes 1 to 4 (DENV1 to -4) extend to the closely related Zika virus (ZIKV). We investigated prospective pediatric cohorts in Nicaragua that experienced sequential DENV1 to -3 (2004 to 2015), Zika (2016 to 2017), and DENV2 (2018 to 2020) epidemics. Risk of symptomatic DENV2 infection and severe disease was elevated by one prior ZIKV infection, one prior DENV infection, or one prior DENV infection followed by one ZIKV infection, compared with being flavivirus-naïve. By contrast, multiple prior DENV infections reduced dengue risk. Further, although high preexisting anti-DENV antibody titers protected against DENV1, DENV3, and ZIKV disease, intermediate titers induced by previous ZIKV or DENV infection enhanced future risk of DENV2 disease and severity, as well as DENV3 severity. The observation that prior ZIKV infection can modulate dengue disease severity like a DENV serotype poses challenges to development of dengue and Zika vaccines.

Modelling the impact of testing, contact tracing and household quarantine on second waves of COVID-19

Alberto Aleta, David Martín-Corral, Ana Pastore y Piontti, Marco Ajelli, Maria Litvinova, Matteo Chinazzi, Natalie E. Dean, M. Elizabeth Halloran, Ira M. Longini, Jr., Stefano Merler, Alex Pentland, Alessandro Vespignani, Esteban Moro, Yamir Moreno

Nature
Human Behaviour

August 5, 2020

ABSTRACT

While severe social-distancing measures have proven effective in slowing the coronavirus disease 2019 (COVID-19) pandemic, second-wave scenarios are likely to emerge as restrictions are lifted. Here we integrate anonymized, geolocalized mobility data with census and demographic data to build a detailed agent-based model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in the Boston metropolitan area. We find that a period of strict social distancing followed by a robust level of testing, contact-tracing and household quarantine could keep the disease within the capacity of the healthcare system while enabling the reopening of economic activities. Our results show that a response system based on enhanced testing and contact tracing can have a major role in relaxing social-distancing interventions in the absence of herd immunity against SARS-CoV-2.

Achieving coordinated national immunity and cholera elimination in Haiti through vaccination: a modelling study

Elizabeth C Lee, Dennis L Chao, Joseph C Lemaitre, Laura Matrajt, Damiano Pasetto, Javier Perez-Saez, Flavio Finger, Andrea Rinaldo, Jonathan D Sugimoto, M Elizabeth Halloran, Ira M Longini, Ralph Ternier, Kenia Vissieres, Andrew S Azman, Justin Lessler, Louise C Ivers

Lancet Global Health

August 1, 2020

ABSTRACT

Background

Cholera was introduced into Haiti in 2010. Since then, more than 820 000 cases and nearly 10 000 deaths have been reported. Oral cholera vaccine (OCV) is safe and effective, but has not been seen as a primary tool for cholera elimination due to a limited period of protection and constrained supplies. Regionally, epidemic cholera is contained to the island of Hispaniola, and the lowest numbers of cases since the epidemic began were reported in 2019. Hence, Haiti may represent a unique opportunity to eliminate cholera with OCV.

Methods

In this modelling study, we assessed the probability of elimination, time to elimination, and percentage of cases averted with OCV campaign scenarios in Haiti through simulations from four modelling teams. For a 10-year period from January 19, 2019, to Jan 13, 2029, we compared a no vaccination scenario with five OCV campaign scenarios that differed in geographical scope, coverage, and rollout duration. Teams used weekly department-level reports of suspected cholera cases from the Haiti Ministry of Public Health and Population to calibrate the models and used common vaccine-related assumptions, but other model features were determined independently.

Findings

Among campaigns with the same vaccination coverage (70% fully vaccinated), the median probability of elimination after 5 years was 0–18% for no vaccination, 0–33% for 2-year campaigns focused in the two departments with the highest historical incidence, 0–72% for three-department campaigns, and 35–100% for nationwide campaigns. Two-department campaigns averted a median of 12–58% of infections, three-department campaigns averted 29–80% of infections, and national campaigns averted 58–95% of infections. Extending the national campaign to a 5-year rollout (compared to a 2-year rollout), reduced the probability of elimination to 0–95% and the proportion of cases averted to 37–86%.

Interpretation

Models suggest that the probability of achieving zero transmission of Vibrio cholerae in Haiti with current methods of control is low, and that bolder action is needed to promote elimination of cholera from the region. Large-scale cholera vaccination campaigns in Haiti would offer the opportunity to synchronise nationwide immunity, providing near-term population protection while improvements to water and sanitation promote long-term cholera elimination.

Estimating the establishment of local transmission and the cryptic phase of the COVID-19 pandemic in the USA

Jessica T. Davis, Matteo Chinazzi, Nicola Perra, Kunpeng Mu, Ana Pastore y Piontti, Marco Ajelli, Natalie E. Dean, Corrado Gioannini, Maria Litvinova, Stefano Merler, Luca Rossi, Kaiyuan Sun, Xinyue Xiong, M. Elizabeth Halloran, Ira M. Longini Jr., Cecile Viboud, Alessandro Vespignani

medRxiv

July 7, 2020

ABSTRACT

We use a global metapopulation transmission model to study the establishment of sustained and undetected community transmission of the COVID-19 epidemic in the United States. The model is calibrated on international case importations from mainland China and takes into account travel restrictions to and from international destinations. We estimate widespread community transmission of SARS-CoV-2 in February, 2020. Modeling results indicate international travel as the key driver of the introduction of SARS-CoV-2 in the West and East Coast metropolitan areas that could have been seeded as early as late-December, 2019. For most of the continental states the largest contribution of imported infections arrived through domestic travel flows.

Household secondary attack rate of COVID-19 and associated determinants in Guangzhou, China: a retrospective cohort study

Qin-Long Jing, Ming-Jin Liu, Jun Yuan, Zhou-Bin Zhang, An-Ran Zhang, Natalie E Dean, Lei Luo, Meng-Meng Ma, Ira Longini, Eben Kenah, Ying Lu, Yu Ma, Neda Jalali, Li-Qun Fang, Zhi-Cong Yang, Yang Yang

Lancet Infectious Diseases

June 17, 2020

ABSTRACT

Background: As of April 2, 2020, the global reported number of COVID-19 cases has crossed over 1 million with more than 55,000 deaths. The household transmissibility of SARS-CoV-2, the causative pathogen, remains elusive. Methods: Based on a comprehensive contact-tracing dataset from Guangzhou, we estimated both the population-level effective reproductive number and individual-level secondary attack rate (SAR) in the household setting. We assessed age effects on transmissibility and the infectivity of COVID-19 cases during their incubation period. Results: A total of 195 unrelated clusters with 212 primary cases, 137 nonprimary (secondary or tertiary) cases and 1938 uninfected close contacts were traced. We estimated the household SAR to be 13.8% (95% CI: 11.1-17.0%) if household contacts are defined as all close relatives and 19.3% (95% CI: 15.5-23.9%) if household contacts only include those at the same residential address as the cases, assuming a mean incubation period of 4 days and a maximum infectious period of 13 days. The odds of infection among children (<20 years old) was only 0.26 (95% CI: 0.13-0.54) times of that among the elderly (≥60 years old). There was no gender difference in the risk of infection. COVID-19 cases were at least as infectious during their incubation period as during their illness. On average, a COVID-19 case infected 0.48 (95% CI: 0.39-0.58) close contacts. Had isolation not been implemented, this number increases to 0.62 (95% CI: 0.51-0.75). The effective reproductive number in Guangzhou dropped from above 1 to below 0.5 in about 1 week. Conclusion: SARS-CoV-2 is more transmissible in households than SARS-CoV and MERS-CoV, and the elderly ≥60 years old are the most vulnerable to household transmission. Case finding and isolation alone may be inadequate to contain the pandemic and need to be used in conjunction with heightened restriction of human movement as implemented in Guangzhou.

The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak

Matteo Chinazzi, Jessica T. Davis, Marco Ajelli, Corrado Gioannini, Maria Litvinova, Stefano Merler, Ana Pastore y Piontti, Luca Rossi, Kaiyuan Sun, Cécile Viboud, Xinyue Xiong, Hongjie Yu, M. Elizabeth Halloran, Ira M. Longini Jr., Alessandro Vespignani

Science

April 24, 2020

ABSTRACT

Motivated by the rapid spread of coronavirus disease 2019 (COVID-19) in mainland China, we use a global metapopulation disease transmission model to project the impact of travel limitations on the national and international spread of the epidemic. The model is calibrated on the basis of internationally reported cases and shows that, at the start of the travel ban from Wuhan on 23 January 2020, most Chinese cities had already received many infected travelers. The travel quarantine of Wuhan delayed the overall epidemic progression by only 3 to 5 days in mainland China but had a more marked effect on the international scale, where case importations were reduced by nearly 80% until mid-February. Modeling results also indicate that sustained 90% travel restrictions to and from mainland China only modestly affect the epidemic trajectory unless combined with a 50% or higher reduction of transmission in the community.

Creating a Framework for Conducting Randomized Clinical Trials during Disease Outbreaks

Natalie E. Dean, Pierre-Stéphane Gsell, Ron Brookmeyer, Forrest W. Crawford, Christl A. Donnelly, Susan S. Ellenberg, Thomas R. Fleming, M. Elizabeth Halloran, Peter Horby, Thomas Jaki, Philip R. Krause, Ira M. Longini, Sabue Mulangu, Jean-Jacques Muyembe-Tamfum, Martha C. Nason, Peter G. Smith, Rui Wang, Ana M. Henao-Restrepo, Victor De Gruttola.

New England Journal of Medicine

April 2, 2020

ABSTRACT

Conducting trials of novel interventions during infectious disease emergencies, such as the ongoing Covid-19 pandemic, is increasingly recognized as important for determining the efficacy of potential vaccines and therapies. Clinical trials to evaluate investigational interventions are being implemented as part of the broader efforts to control the spread of an infectious disease and to improve patient outcomes. In such circumstances, however, it can be challenging to acquire the necessary evidence about the effects of the interventions to inform future patient care and public health planning, in part because of the unpredictable size, geographic location, and duration of outbreaks.

Evolving epidemiology and transmission dynamics of coronavirus disease 2019 outside Hubei province, China: a descriptive and modelling study

Juanjuan Zhang, Maria Litvinova, Wei Wang, Yan Wang, Xiaowei Deng, Xinghui Chen, Mei Li, Wen Zheng, Lan Yi, Xinhua Chen, Qianhui Wu, Yuxia Liang, Xiling Wang, Juan Yang, Kaiyuan Sun, Ira M Longini Jr, M Elizabeth Halloran, Peng Wu, Benjamin J Cowling, Stefano Merler, Cecile Viboud, Alessandro Vespignani, Marco Ajelli, Hongjie Yu

Lancet Infectious Diseases

April 2, 2020

ABSTRACT

Background

The coronavirus disease 2019 (COVID-19) epidemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), began in Wuhan city, Hubei province, in December, 2019, and has spread throughout China. Understanding the evolving epidemiology and transmission dynamics of the outbreak beyond Hubei would provide timely information to guide intervention policy.

Methods

We collected individual information from official public sources on laboratory-confirmed cases reported outside Hubei in mainland China for the period of Jan 19 to Feb 17, 2020. We used the date of the fourth revision of the case definition (Jan 27) to divide the epidemic into two time periods (Dec 24 to Jan 27, and Jan 28 to Feb 17) as the date of symptom onset. We estimated trends in the demographic characteristics of cases and key time-to-event intervals. We used a Bayesian approach to estimate the dynamics of the net reproduction number (Rt) at the provincial level.

Findings

We collected data on 8579 cases from 30 provinces. The median age of cases was 44 years (33–56), with an increasing proportion of cases in younger age groups and in elderly people (ie, aged >64 years) as the epidemic progressed. The mean time from symptom onset to hospital admission decreased from 4·4 days (95% CI 0·0–14·0) for the period of Dec 24 to Jan 27, to 2·6 days (0·0–9·0) for the period of Jan 28 to Feb 17. The mean incubation period for the entire period was estimated at 5·2 days (1·8–12·4) and the mean serial interval at 5·1 days (1·3–11·6). The epidemic dynamics in provinces outside Hubei were highly variable but consistently included a mixture of case importations and local transmission. We estimated that the epidemic was self-sustained for less than 3 weeks, with mean Rt reaching peaks between 1·08 (95% CI 0·74–1·54) in Shenzhen city of Guangdong province and 1·71 (1·32–2·17) in Shandong province. In all the locations for which we had sufficient data coverage of Rt, Rt was estimated to be below the epidemic threshold (ie, <1) after Jan 30.

Interpretation

Our estimates of the incubation period and serial interval were similar, suggesting an early peak of infectiousness, with possible transmission before the onset of symptoms. Our results also indicate that, as the epidemic progressed, infectious individuals were isolated more quickly, thus shortening the window of transmission in the community. Overall, our findings indicate that strict containment measures, movement restrictions, and increased awareness of the population might have contributed to interrupt local transmission of SARS-CoV-2 outside Hubei province.

Aggregated mobility data could help fight COVID-19

Caroline O. Buckee, Satchit Balsari, Jennifer Chan, Mercè Crosas, Francesca Dominici, Urs Gasser, Yonatan H. Grad, Bryan Grenfell, M. Elizabeth Halloran, Moritz U. G. Kraemer, Marc Lipsitch, C. Jessica E. Metcalf, Lauren Ancel Meyers, T. Alex Perkins, Mauricio Santillana, Samuel V. Scarpino, Cecile Viboud, Amy Wesolowski, Andrew Schroeder

Science

March 23, 2020

ABSTRACT

As the coronavirus disease (COVID-19) epidemic worsens, understanding the effectiveness of public messaging and large-scale social distancing interventions is critical. The research and public health response communities can and should use population mobility data collected by private companies, with appropriate legal, organizational, and computational safeguards in place. When aggregated, these data can help refine interventions by providing near real-time information about changes in patterns of human movement.

Detecting critical slowing down in high-dimensional epidemiological systems

Tobias Brett, Marco Ajelli, Quan-Hui Liu, Mary G. Krauland, John J. Grefenstette, Willem G. van Panhuis, Alessandro Vespignani, John M. Drake, Pejman Rohani

PLOS Computational Biology

March 9, 2020

ABSTRACT

Despite medical advances, the emergence and re-emergence of infectious diseases continue to pose a public health threat. Low-dimensional epidemiological models predict that epidemic transitions are preceded by the phenomenon of critical slowing down (CSD). This has raised the possibility of anticipating disease (re-)emergence using CSD-based early-warning signals (EWS), which are statistical moments estimated from time series data. For EWS to be useful at detecting future (re-)emergence, CSD needs to be a generic (model-independent) feature of epidemiological dynamics irrespective of system complexity. Currently, it is unclear whether the predictions of CSD—derived from simple, low-dimensional systems—pertain to real systems, which are high-dimensional. To assess the generality of CSD, we carried out a simulation study of a hierarchy of models, with increasing structural complexity and dimensionality, for a measles-like infectious disease. Our five models included: i) a nonseasonal homogeneous Susceptible-Exposed-Infectious-Recovered (SEIR) model, ii) a homogeneous SEIR model with seasonality in transmission, iii) an age-structured SEIR model, iv) a multiplex network-based model (Mplex) and v) an agent-based simulator (FRED). All models were parameterised to have a herd-immunity immunization threshold of around 90% coverage, and underwent a linear decrease in vaccine uptake, from 92% to 70% over 15 years. We found evidence of CSD prior to disease re-emergence in all models. We also evaluated the performance of seven EWS: the autocorrelation, coefficient of variation, index of dispersion, kurtosis, mean, skewness, variance. Performance was scored using the Area Under the ROC Curve (AUC) statistic. The best performing EWS were the mean and variance, with AUC > 0.75 one year before the estimated transition time. These two, along with the autocorrelation and index of dispersion, are promising candidate EWS for detecting disease emergence.

Inferring high-resolution human mixing patterns for disease modeling

Dina Mistry, Maria Litvinova, Ana Pastore y Piontti, Matteo Chinazzi, Laura Fumanelli, Marcelo F. C. Gomes, Syed A. Haque, Quan-Hui Liu, Kunpeng Mu, Xinyue Xiong, M. Elizabeth Halloran, Ira M. Longini Jr., Stefano Merler, Marco Ajelli, Alessandro Vespignani

arXiv

March 4, 2020

ABSTRACT

Mathematical and computational modeling approaches are increasingly used as quantitative tools in the analysis and forecasting of infectious disease epidemics. The growing need for realism in addressing complex public health questions is however calling for accurate models of the human contact patterns that govern the disease transmission processes. Here we present a data-driven approach to generate effective descriptions of population-level contact patterns by using highly detailed macro (census) and micro (survey) data on key socio-demographic features. We produce age-stratified contact matrices for 277 sub-national administrative regions of countries covering approximately 3.5 billion people and reflecting the high degree of cultural and societal diversity of the focus countries. We use the derived contact matrices to model the spread of airborne infectious diseases and show that sub-national heterogeneities in human mixing patterns have a marked impact on epidemic indicators such as the reproduction number and overall attack rate of epidemics of the same etiology. The contact patterns derived here are made publicly available as a modeling tool to study the impact of socio-economic differences and demographic heterogeneities across populations on the epidemiology of infectious diseases.

Evolving epidemiology of novel coronavirus diseases 2019 and possible interruption of local transmission outside Hubei Province in China: a descriptive and modeling study

Juanjuan Zhang, Maria Litvinova, Wei Wang, Yan Wang, Xiaowei Deng, Xinghui Chen, Mei Li, Wen Zheng, Lan Yi, Xinhua Chen, Qianhui Wu, Yuxia Liang, Xiling Wang, Juan Yang, Kaiyuan Sun, Ira M. Longini Jr., M. Elizabeth Halloran, Peng Wu, Benjamin J. Cowling, Stefano Merler, Cecile Viboud, Alessandro Vespignani, Marco Ajelli, Hongjie Yu

medRxiv

February 23, 2020

ABSTRACT

Background: The COVID-19 epidemic originated in Wuhan City of Hubei Province in December 2019 and has spread throughout China. Understanding the fast evolving epidemiology and transmission dynamics of the outbreak beyond Hubei would provide timely information to guide intervention policy.

Methods: We collected individual information on 8,579 laboratory-confirmed cases from official publically sources reported outside Hubei in mainland China, as of February 17, 2020. We estimated the temporal variation of the demographic characteristics of cases and key time-to-event intervals. We used a Bayesian approach to estimate the dynamics of the net reproduction number (Rt) at the provincial level.

Results: The median age of the cases was 44 years, with an increasing of cases in younger age groups and the elderly as the epidemic progressed. The delay from symptom onset to hospital admission decreased from 4.4 days (95%CI: 0.0-14.0) until January 27 to 2.6 days (0.0-9.0) from January 28 to February 17. The mean incubation period was estimated at 5.2 days (1.8-12.4) and the mean serial interval at 5.1 days (1.3-11.6). The epidemic dynamics in provinces outside Hubei was highly variable, but consistently included a mix of case importations and local transmission. We estimate that the epidemic was self-sustained for less than three weeks with Rt reaching peaks between 1.40 (1.04-1.85) in Shenzhen City of Guangdong Province and 2.17 (1.69-2.76) in Shandong Province. In all the analyzed locations (n=10) Rt was estimated to be below the epidemic threshold since the end of January.

Conclusion: Our findings suggest that the strict containment measures and movement restrictions in place may contribute to the interruption of local COVID-19 transmission outside Hubei Province. The shorter serial interval estimated here implies that transmissibility is not as high as initial estimates suggested.

Designing effective control of dengue with combined interventions

Thomas J. Hladish, Carl A. B. Pearson, Kok Ben Toh, Diana Patricia Rojas, Pablo Manrique-Saide, Gonzalo M. Vazquez-Prokopec, M. Elizabeth Halloran, Ira M. Longini Jr

PNAS

January 23, 2020

ABSTRACT

Viruses transmitted by Aedes mosquitoes, such as dengue, Zika, and chikungunya, have expanding ranges and seem unabated by current vector control programs. Effective control of these pathogens likely requires integrated approaches. We evaluated dengue management options in an endemic setting that combine novel vector control and vaccination using an agent-based model for Yucatán, Mexico, fit to 37 y of data. Our intervention models are informed by targeted indoor residual spraying (TIRS) experiments; trial outcomes and World Health Organization (WHO) testing guidance for the only licensed dengue vaccine, CYD-TDV; and preliminary results for in-development vaccines. We evaluated several implementation options, including varying coverage levels; staggered introductions; and a one-time, large-scale vaccination campaign. We found that CYD-TDV and TIRS interfere: while the combination outperforms either alone, performance is lower than estimated from their separate benefits. The conventional model hypothesized for in-development vaccines, however, performs synergistically with TIRS, amplifying effectiveness well beyond their independent impacts. If the preliminary performance by either of the in-development vaccines is upheld, a one-time, large-scale campaign followed by routine vaccination alongside aggressive new vector control could enable short-term elimination, with nearly all cases avoided for a decade despite continuous dengue reintroductions. If elimination is impracticable due to resource limitations, less ambitious implementations of this combination still produce amplified, longer-lasting effectiveness over single-approach interventions.

Designing a Study of Correlates of Risk for Ebola Vaccination

M. Elizabeth Halloran, Ira M. Longini, Peter B. Gilbert

American Journal of Epidemiology

January 23, 2020

ABSTRACT

The rVSV Ebola vaccine was shown to be very efficacious in a novel ring vaccination trial in Guinea. However, no correlates of vaccine protection have been established for Ebola vaccines. Several Ebola vaccine candidates are available, but conducting randomized trials of additional candidates in outbreaks is difficult. Establishing correlates of vaccine protection is essential. Here we explore power and sample size calculations to evaluate potential correlates of risk during an Ebola vaccination campaignin an outbreak. The method requires a blood draw be made at a predetermined time after vaccination. The statistical analysis estimates the relative risk of the Ebola endpoint occurring after the blood draw through to the end of follow-up, contrasting vaccine recipients with different values of the immune response marker. The analysis can be done assuming a trichotomous or continuous marker. Under certain assumptions, at an overall vaccine efficacy of 75%, 50 Ebola endpoints in the vaccinees provided good power. At an overall vaccine efficacy of 90%, 20 Ebola endpoints gave good power. Power was highest when more vaccinees were in the high and low responder groups versus the middle group and when vaccine efficacy differed the most between the high and low responder groups.

Preliminary assessment of the International Spreading Risk Associated with the 2019 novel Coronavirus (2019-nCoV) outbreak in Wuhan City

Matteo Chinazzi, Jessica T. Davis, Corrado Gioannini, Maria Litvinova, Ana Pastore y Piontti, Luca Rossi, Xinyue Xiong, M. Elizabeth Halloran, Ira M. Longini Jr., Alessandro Vespignani

MOBS Lab 2019 nCOV website

January 17, 2020

ABSTRACT

Starting in December 2019, Chinese health authorities have been closely monitoring a cluster of pneumonia cases in the city of Wuhan, in Hubei Province. It has been determined that the pathogen causing the viral pneumonia among affected individuals is a new coronavirus (2019-nCoV)(1). As of January 17, 2020, 45 cases have been detected and confirmed in the region(2) with 3 additional cases detected and confirmed in Japan and Thailand(3; 4). The source of the outbreak is still unknown, however investigations have identified environmental samples that tested positive for 2019-nCoV at the Huanan Seafood Wholesale Market in Wuhan city. Some of the most recent cases did not report exposure to animal markets, thus suggesting that human-to-human transmission, although limited, is possible. Considering the potential international threat that an outbreak of a novel virus like this one poses to the world, in this report we provide a modeling analysis of the risk of dissemination of 2019- nCoV infections. By using the cases detected outside China, we also provide estimates of the potential outbreak size in Wuhan as of January 17th, 2020.