1
|
Broda MD, Borovska P, Kollenda D, Linka M, de Haas N, de Haas S, de Haas B. Estimating the human bottleneck for contact tracing. PNAS NEXUS 2024; 3:pgae283. [PMID: 39076682 PMCID: PMC11285183 DOI: 10.1093/pnasnexus/pgae283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 07/05/2024] [Indexed: 07/31/2024]
Abstract
The SARS-CoV-2 pandemic has highlighted the importance of contact tracing for epidemiological mitigation. Contact tracing interviews (CTIs) typically rely on episodic memory, which is prone to decline over time. Here, we provide a quantitative estimate of reporting decline for age- and gender-representative samples from the United Kingdom and Germany, emulating >15,000 CTIs. We find that the number of reported contacts declines as a power function of recall delay and is significantly higher for younger subjects and for those who used memory aids, such as a scheduler. We further find that these factors interact with delay: Older subjects and those who made no use of memory aids have steeper decline functions. These findings can inform epidemiological modeling and policies in the context of infectious diseases.
Collapse
Affiliation(s)
- Maximilian D Broda
- Experimental Psychology, Justus Liebig University Giessen, Otto-Behaghel-Str 10F, 35394 Giessen, Germany
- Center for Mind, Brain and Behavior, Universities of Marburg, Giessen and Darmstadt, Hans-Meerwein-Strasse 6, 35032 Marburg, Germany
| | - Petra Borovska
- Experimental Psychology, Justus Liebig University Giessen, Otto-Behaghel-Str 10F, 35394 Giessen, Germany
| | - Diana Kollenda
- Experimental Psychology, Justus Liebig University Giessen, Otto-Behaghel-Str 10F, 35394 Giessen, Germany
| | - Marcel Linka
- Experimental Psychology, Justus Liebig University Giessen, Otto-Behaghel-Str 10F, 35394 Giessen, Germany
| | | | - Samuel de Haas
- Chair for Industrial Organization, Regulation and Antitrust, Department of Economics, Justus Liebig University Giessen, Licher Straße 62, 35394 Giessen, Germany
| | - Benjamin de Haas
- Experimental Psychology, Justus Liebig University Giessen, Otto-Behaghel-Str 10F, 35394 Giessen, Germany
- Center for Mind, Brain and Behavior, Universities of Marburg, Giessen and Darmstadt, Hans-Meerwein-Strasse 6, 35032 Marburg, Germany
| |
Collapse
|
2
|
Ladib M, Ouhinou A, Yakubu AA. Mathematical modeling of contact tracing and stability analysis to inform its impact on disease outbreaks; an application to COVID-19. Infect Dis Model 2024; 9:329-353. [PMID: 38371875 PMCID: PMC10867662 DOI: 10.1016/j.idm.2024.01.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 01/29/2024] [Accepted: 01/29/2024] [Indexed: 02/20/2024] Open
Abstract
We develop a mathematical model to investigate the effect of contact tracing on containing epidemic outbreaks and slowing down the spread of transmissible diseases. We propose a discrete-time epidemic model structured by disease-age which includes general features of contact tracing. The model is fitted to data reported for the early spread of COVID-19 in South Korea, Brazil, and Venezuela. The calibrated values for the contact tracing parameters reflect the order pattern observed in its performance intensity within the three countries. Using the fitted values, we estimate the effective reproduction number R e and investigate its responses to varied control scenarios of contact tracing. Alongside the positivity of solutions, and a stability analysis of the disease-free equilibrium are provided.
Collapse
Affiliation(s)
- Mohamed Ladib
- University of Sultan Moulay Slimane, Faculty of Sciences and Techniques, Team of Mathematics and Interactions, Béni-Mellal, Morocco
| | - Aziz Ouhinou
- University of Sultan Moulay Slimane, Faculty of Sciences and Techniques, Team of Mathematics and Interactions, Béni-Mellal, Morocco
| | | |
Collapse
|
3
|
Kwak M, Sun X, Wi Y, Nah K, Kim Y, Jin H. A novel indicator in epidemic monitoring through a case study of Ebola in West Africa (2014-2016). Sci Rep 2024; 14:12147. [PMID: 38802461 PMCID: PMC11130319 DOI: 10.1038/s41598-024-62719-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 05/21/2024] [Indexed: 05/29/2024] Open
Abstract
The E/S (exposed/susceptible) ratio is analyzed in the SEIR model. The ratio plays a key role in understanding epidemic dynamics during the 2014-2016 Ebola outbreak in Sierra Leone and Guinea. The maximum value of the ratio occurs immediately before or after the time-dependent reproduction number (Rt) equals 1, depending on the initial susceptible population (S(0)). It is demonstrated that transmission rate curves corresponding to various incubation periods intersect at a single point referred to as the Cross Point (CP). At this point, the E/S ratio reaches an extremum, signifying a critical shift in transmission dynamics and aligning with the time when Rt approaches 1. By plotting transmission rate curves, β(t), for any two arbitrary incubation periods and tracking their intersections, we can trace CP over time. CP serves as an indicator of epidemic status, especially when Rt is close to 1. It provides a practical means of monitoring epidemics without prior knowledge of the incubation period. Through a case study, we estimate the transmission rate and reproduction number, identifying CP and Rt = 1 while examining the E/S ratio across various values of S(0).
Collapse
Affiliation(s)
- Minkyu Kwak
- Department of Mathematics and Statistics, Chonnam National University, Gwangju, South Korea
| | - Xiuxiu Sun
- Department of Mathematics and Physics, Luoyang Institute of Science and Technology, Henan, China
| | - Yunju Wi
- Department of Mathematics and Statistics, Chonnam National University, Gwangju, South Korea
| | - Kyeongah Nah
- Busan Center for Medical Mathematics, National Institute of Mathematical Sciences, Busan, South Korea
| | - Yongkuk Kim
- Department of Mathematics, Kyungpook National University, Daegu, South Korea
| | - Hongsung Jin
- Department of Mathematics and Statistics, Chonnam National University, Gwangju, South Korea.
| |
Collapse
|
4
|
Wanyana MW, Akunzirwe R, King P, Atuhaire I, Zavuga R, Lubwama B, Kabami Z, Ahirirwe SR, Ninsiima M, Naiga HN, Zalwango JF, Zalwango MG, Kawungezi PC, Simbwa BN, Kizito SN, Kiggundu T, Agaba B, Migisha R, Kadobera D, Kwesiga B, Bulage L, Ario AR, Harris JR. Performance and impact of contact tracing in the Sudan virus outbreak in Uganda, September 2022-January 2023. Int J Infect Dis 2024; 141:106959. [PMID: 38340782 DOI: 10.1016/j.ijid.2024.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 02/01/2024] [Accepted: 02/05/2024] [Indexed: 02/12/2024] Open
Abstract
BACKGROUND Contact tracing (CT) is critical for ebolavirus outbreak response. Ideally, all new cases after the index case should be previously-known contacts (PKC) before their onset, and spend minimal time ill in the community. We assessed the impact of CT during the 2022 Sudan Virus Disease (SVD) outbreak in Uganda. METHODS We collated anonymized data from the SVD case and contacts database to obtain and analyze data on CT performance indicators, comparing confirmed cases that were PKC and were not PKC (NPKC) before onset. We assessed the effect of being PKC on the number of people infected using Poisson regression. RESULTS There were 3844 contacts of 142 confirmed cases (mean: 22 contacts/case). Forty-seven (33%) confirmed cases were PKC. PKCs had fewer median days from onset to isolation (4 vs 6; P<0.007) and laboratory confirmation (4 vs 7; P<0.001) than NPKC. Being a PKC vs NPKC reduced risk of transmitting infection by 84% (IRR=0.16, 95% CI 0.08-0.32). CONCLUSION Contact identification was sub-optimal during the outbreak. However, CT reduced the time SVD cases spent in the community before isolation and the number of persons infected in Uganda. Approaches to improve contact tracing, especially contact listing, may improve control in future outbreaks.
Collapse
Affiliation(s)
- Mercy Wendy Wanyana
- Uganda Public Health Fellowship Program-Uganda National Institute of Public Health, Kampala, Uganda.
| | - Rebecca Akunzirwe
- Uganda Public Health Fellowship Program-Uganda National Institute of Public Health, Kampala, Uganda
| | - Patrick King
- Uganda Public Health Fellowship Program-Uganda National Institute of Public Health, Kampala, Uganda
| | - Immaculate Atuhaire
- Uganda Public Health Fellowship Program-Uganda National Institute of Public Health, Kampala, Uganda
| | - Robert Zavuga
- Uganda Public Health Fellowship Program-Uganda National Institute of Public Health, Kampala, Uganda
| | | | - Zainah Kabami
- Uganda Public Health Fellowship Program-Uganda National Institute of Public Health, Kampala, Uganda
| | - Sherry Rita Ahirirwe
- Uganda Public Health Fellowship Program-Uganda National Institute of Public Health, Kampala, Uganda
| | - Mackline Ninsiima
- Uganda Public Health Fellowship Program-Uganda National Institute of Public Health, Kampala, Uganda
| | - Hellen Nelly Naiga
- Uganda Public Health Fellowship Program-Uganda National Institute of Public Health, Kampala, Uganda
| | - Jane Frances Zalwango
- Uganda Public Health Fellowship Program-Uganda National Institute of Public Health, Kampala, Uganda
| | - Marie Gorreti Zalwango
- Uganda Public Health Fellowship Program-Uganda National Institute of Public Health, Kampala, Uganda
| | - Peter Chris Kawungezi
- Uganda Public Health Fellowship Program-Uganda National Institute of Public Health, Kampala, Uganda
| | - Brenda Nakafeero Simbwa
- Uganda Public Health Fellowship Program-Uganda National Institute of Public Health, Kampala, Uganda
| | - Saudah Namubiru Kizito
- Uganda Public Health Fellowship Program-Uganda National Institute of Public Health, Kampala, Uganda
| | - Thomas Kiggundu
- Uganda Public Health Fellowship Program-Uganda National Institute of Public Health, Kampala, Uganda
| | - Brian Agaba
- Uganda Public Health Fellowship Program-Uganda National Institute of Public Health, Kampala, Uganda
| | - Richard Migisha
- Uganda Public Health Fellowship Program-Uganda National Institute of Public Health, Kampala, Uganda
| | - Daniel Kadobera
- Uganda Public Health Fellowship Program-Uganda National Institute of Public Health, Kampala, Uganda
| | - Benon Kwesiga
- Uganda Public Health Fellowship Program-Uganda National Institute of Public Health, Kampala, Uganda
| | - Lilian Bulage
- Uganda Public Health Fellowship Program-Uganda National Institute of Public Health, Kampala, Uganda
| | | | - Julie R Harris
- Division of Global Health Protection, US Centers for Disease Control and Prevention, Kampala, Uganda
| |
Collapse
|
5
|
Heidecke J, Fuhrmann J, Barbarossa MV. A mathematical model to assess the effectiveness of test-trace-isolate-and-quarantine under limited capacities. PLoS One 2024; 19:e0299880. [PMID: 38470895 DOI: 10.1371/journal.pone.0299880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 02/17/2024] [Indexed: 03/14/2024] Open
Abstract
Diagnostic testing followed by isolation of identified cases with subsequent tracing and quarantine of close contacts-often referred to as test-trace-isolate-and-quarantine (TTIQ) strategy-is one of the cornerstone measures of infectious disease control. The COVID-19 pandemic has highlighted that an appropriate response to outbreaks of infectious diseases requires a firm understanding of the effectiveness of such containment strategies. To this end, mathematical models provide a promising tool. In this work, we present a delay differential equation model of TTIQ interventions for infectious disease control. Our model incorporates the assumption of limited TTIQ capacities, providing insights into the reduced effectiveness of testing and tracing in high prevalence scenarios. In addition, we account for potential transmission during the early phase of an infection, including presymptomatic transmission, which may be particularly adverse to a TTIQ based control. Our numerical experiments inspired by the early spread of COVID-19 in Germany demonstrate the effectiveness of TTIQ in a scenario where immunity within the population is low and pharmaceutical interventions are absent, which is representative of a typical situation during the (re-)emergence of infectious diseases for which therapeutic drugs or vaccines are not yet available. Stability and sensitivity analyses reveal both disease-dependent and disease-independent factors that impede or enhance the success of TTIQ. Studying the diminishing impact of TTIQ along simulations of an epidemic wave, we highlight consequences for intervention strategies.
Collapse
Affiliation(s)
- Julian Heidecke
- Frankfurt Institute for Advanced Studies, Frankfurt, Germany
- Interdisciplinary Center for Scientific Computing, Heidelberg University, Heidelberg, Germany
- Heidelberg Institute of Global Health, Heidelberg University, Heidelberg, Germany
| | - Jan Fuhrmann
- Institute of Applied Mathematics, Heidelberg University, Heidelberg, Germany
| | | |
Collapse
|
6
|
Hijano DR, Dennis SR, Hoffman JM, Tang L, Hayden RT, Gaur AH, Hakim H. Employee investigation and contact tracing program in a pediatric cancer hospital to mitigate the spread of COVID-19 among the workforce, patients, and caregivers. Front Public Health 2024; 11:1304072. [PMID: 38259752 PMCID: PMC10801179 DOI: 10.3389/fpubh.2023.1304072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 12/18/2023] [Indexed: 01/24/2024] Open
Abstract
Background Case investigations and contact tracing are essential disease control measures used by health departments. Early in the pandemic, they were seen as a key strategy to stop COVID-19 spread. The CDC urged rapid action to scale up and train a large workforce and collaborate across public and private agencies to halt COVID-19 transmission. Methods We developed a program for case investigation and contact tracing that followed CDC and local health guidelines, compliant with the Occupational Safety and Health Administration (OSHA) regulations and tailored to the needs and resources of our institution. Program staff were trained and assessed for competency before joining the program. Results From March 2020 to May 2021, we performed 838 COVID-19 case investigations, which led to 136 contacts. Most employees reported a known SARS-CoV-2 exposure from the community (n = 435) or household (n = 343). Only seven (5.1%) employees were determined as more likely than not to have SARS-CoV-2 infection related to workplace exposure, and when so, lapses in following the masking recommendations were identified. Between June 2021-February 2022, our program adjusted to the demand of the different waves, particularly omicron, by significantly reducing the amount of data collected. No transmission from employees to patients or caregivers was observed during this period. Conclusion Prompt implementation of case investigation and contact tracing is possible, and it effectively reduces workplace exposures. This approach can be adapted to suit the specific needs and requirements of various healthcare settings, particularly those serving the most vulnerable patient populations.
Collapse
Affiliation(s)
- Diego R. Hijano
- Departments of Infectious Diseases, St. Jude Children’s Research Hospital, Memphis, TN, United States
- Department of Pediatrics, University of Tennessee Health Sciences Center, Memphis, TN, United States
| | - Sandra R. Dennis
- Department of Human Resources, St. Jude Children’s Research Hospital, Memphis, TN, United States
| | - James M. Hoffman
- Department of Human Resources, St. Jude Children’s Research Hospital, Memphis, TN, United States
| | - Li Tang
- Department of Biostatistics, St. Jude Children’s Research Hospital, Memphis, TN, United States
| | - Randall T. Hayden
- Department of Pathology, St. Jude Children’s Research Hospital, Memphis, TN, United States
| | | | - Aditya H. Gaur
- Departments of Infectious Diseases, St. Jude Children’s Research Hospital, Memphis, TN, United States
| | - Hana Hakim
- Office of Quality and Patient Safety, St. Jude Children’s Research Hospital, Memphis, TN, United States
- Department of Preventive Medicine, University of Tennessee Health Sciences Center, Memphis, TN, United States
| |
Collapse
|
7
|
Muzembo BA, Kitahara K, Mitra D, Ntontolo NP, Ngatu NR, Ohno A, Khatiwada J, Dutta S, Miyoshi SI. The basic reproduction number (R 0) of ebola virus disease: A systematic review and meta-analysis. Travel Med Infect Dis 2024; 57:102685. [PMID: 38181864 DOI: 10.1016/j.tmaid.2023.102685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 12/22/2023] [Accepted: 12/27/2023] [Indexed: 01/07/2024]
Abstract
BACKGROUND Ebola virus disease (Ebola) is highly pathogenic, transmissible, and often deadly, with debilitating consequences. Superspreading within a cluster is also possible. In this study, we aim to document Ebola basic reproduction number (R0): the average number of new cases associated with an Ebola case in a completely susceptible population. METHODS We undertook a systematic review and meta-analysis. We searched PubMed, EMBASE, and Web of Science for studies published between 1976 and February 27, 2023. We also manually searched the reference lists of the reviewed studies to identify additional studies. We included studies that reported R0 during Ebola outbreaks in Africa. We excluded studies that reported only the effective reproduction number (Rt). Abstracting data from included studies was performed using a pilot-tested standard form. Two investigators reviewed the studies, extracted the data, and assessed quality. The pooled R0 was determined by a random-effects meta-analysis. R0 was stratified by country. We also estimated the theoretically required immunization coverage to reach herd-immunity using the formula of (1-1/R0) × 100 %. RESULTS The search yielded 2042 studies. We included 53 studies from six African countries in the systematic review providing 97 Ebola mean R0 estimates. 27 (with 46 data points) studies were included in the meta-analysis. The overall pooled mean Ebola R0 was 1.95 (95 % CI 1.74-2.15), with high heterogeneity (I2 = 99.99 %; τ2 = 0.38; and p < 0.001) and evidence of small-study effects (Egger's statistics: Z = 4.67; p < 0.001). Mean Ebola R0 values ranged from 1.2 to 10.0 in Nigeria, 1.1 to 7 in Guinea, 1.14 to 8.33 in Sierra Leone, 1.13 to 5 in Liberia, 1.2 to 5.2 in DR Congo, 1.34 to 2.7 in Uganda, and from 1.40 to 2.55 for all West African countries combined. Pooled mean Ebola R0 was 9.38 (95 % CI 4.16-14.59) in Nigeria, 3.31 (95 % CI 2.30-4.32) in DR Congo, 2.0 (95 % CI 1.25-2.76) in Uganda, 1.83 (95 % CI 1.61-2.05) in Liberia, 1.73 (95 % CI 1.47-2.0) in Sierra Leonne, and 1.44 (95 % CI 1.29-1.60) in Guinea. In theory, 50 % of the population needs to be vaccinated to achieve herd immunity, assuming that Ebola vaccine would be 100 % effective. CONCLUSIONS Ebola R0 varies widely across countries. Ebola has a much wider R0 range than is often claimed (1.3-2.0). It is possible for an Ebola index case to infect more than two susceptible individuals.
Collapse
Affiliation(s)
- Basilua Andre Muzembo
- Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan.
| | - Kei Kitahara
- Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan; Collaborative Research Centre of Okayama University for Infectious Diseases in India at ICMR-NICED, Kolkata, India
| | - Debmalya Mitra
- Collaborative Research Centre of Okayama University for Infectious Diseases in India at ICMR-NICED, Kolkata, India
| | - Ngangu Patrick Ntontolo
- Institut Médical Evangélique (IME), Kimpese, Congo; Department of Family Medicine and PHC, Protestant University of Congo, Congo
| | - Nlandu Roger Ngatu
- Department of Public Health, Kagawa University Faculty of Medicine, Miki, Japan
| | - Ayumu Ohno
- Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan; Collaborative Research Centre of Okayama University for Infectious Diseases in India at ICMR-NICED, Kolkata, India
| | | | - Shanta Dutta
- Division of Bacteriology, ICMR-National Institute of Cholera and Enteric Diseases, Kolkata, India
| | - Shin-Ichi Miyoshi
- Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan
| |
Collapse
|
8
|
Juul JL, Strogatz SH. Comparing the efficiency of forward and backward contact tracing. Phys Rev E 2023; 108:034308. [PMID: 37849148 DOI: 10.1103/physreve.108.034308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 06/28/2023] [Indexed: 10/19/2023]
Abstract
Tracing potentially infected contacts of confirmed cases is important when fighting outbreaks of many infectious diseases. The COVID-19 pandemic has motivated researchers to examine how different contact tracing strategies compare in terms of effectiveness (ability to mitigate infections) and cost efficiency (number of prevented infections per isolation). Two important strategies are so-called forward contact tracing (tracing to whom disease spreads) and backward contact tracing (tracing from whom disease spreads). Recently, Kojaku and colleagues reported that backward contact tracing was "profoundly more effective" than forward contact tracing, that contact tracing effectiveness "hinges on reaching the 'source' of infection," and that contact tracing outperformed case isolation in terms of cost efficiency. Here we show that these conclusions are not true in general. They were based in part on simulations that vastly overestimated the effectiveness and efficiency of contact tracing. Our results show that the efficiency of contact tracing strategies is highly contextual; faced with a disease outbreak, the disease dynamics determine whether tracing infection sources or new cases is more impactful. Our results also demonstrate the importance of simulating disease spread and mitigation measures in parallel rather than sequentially.
Collapse
Affiliation(s)
- Jonas L Juul
- Center for Applied Mathematics, Cornell University, Ithaca, New York 14853, USA
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby 2800, Denmark
| | - Steven H Strogatz
- Center for Applied Mathematics, Cornell University, Ithaca, New York 14853, USA
| |
Collapse
|
9
|
Bugalia S, Tripathi JP. Assessing potential insights of an imperfect testing strategy: Parameter estimation and practical identifiability using early COVID-19 data in India. COMMUNICATIONS IN NONLINEAR SCIENCE & NUMERICAL SIMULATION 2023; 123:107280. [PMID: 37207195 PMCID: PMC10148719 DOI: 10.1016/j.cnsns.2023.107280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 02/27/2023] [Accepted: 04/25/2023] [Indexed: 05/21/2023]
Abstract
A deterministic model with testing of infected individuals has been proposed to investigate the potential consequences of the impact of testing strategy. The model exhibits global dynamics concerning the disease-free and a unique endemic equilibrium depending on the basic reproduction number when the recruitment of infected individuals is zero; otherwise, the model does not have a disease-free equilibrium, and disease never dies out in the community. Model parameters have been estimated using the maximum likelihood method with respect to the data of early COVID-19 outbreak in India. The practical identifiability analysis shows that the model parameters are estimated uniquely. The consequences of the testing rate for the weekly new cases of early COVID-19 data in India tell that if the testing rate is increased by 20% and 30% from its baseline value, the weekly new cases at the peak are decreased by 37.63% and 52.90%; and it also delayed the peak time by four and fourteen weeks, respectively. Similar findings are obtained for the testing efficacy that if it is increased by 12.67% from its baseline value, the weekly new cases at the peak are decreased by 59.05% and delayed the peak by 15 weeks. Therefore, a higher testing rate and efficacy reduce the disease burden by tumbling the new cases, representing a real scenario. It is also obtained that the testing rate and efficacy reduce the epidemic's severity by increasing the final size of the susceptible population. The testing rate is found more significant if testing efficacy is high. Global sensitivity analysis using partial rank correlation coefficients (PRCCs) and Latin hypercube sampling (LHS) determine the key parameters that must be targeted to worsen/contain the epidemic.
Collapse
Affiliation(s)
- Sarita Bugalia
- Department of Mathematics, Central University of Rajasthan, Bandar Sindri, Kishangarh 305817, Ajmer, Rajasthan, India
| | - Jai Prakash Tripathi
- Department of Mathematics, Central University of Rajasthan, Bandar Sindri, Kishangarh 305817, Ajmer, Rajasthan, India
| |
Collapse
|
10
|
Müller J, Hösel V. Contact tracing & super-spreaders in the branching-process model. J Math Biol 2023; 86:24. [PMID: 36625934 PMCID: PMC9830628 DOI: 10.1007/s00285-022-01857-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Revised: 07/18/2021] [Accepted: 07/21/2021] [Indexed: 01/11/2023]
Abstract
In recent years, it became clear that super-spreader events play an important role, particularly in the spread of airborne infections. We investigate a novel model for super-spreader events, not based on a heterogeneous contact graph but on a random contact rate: Many individuals become infected synchronously in single contact events. We use the branching-process approach for contact tracing to analyze the impact of super-spreader events on the effect of contact tracing. Here we neglect a tracing delay. Roughly speaking, we find that contact tracing is more efficient in the presence of super-spreaders if the fraction of symptomatics is small, the tracing probability is high, or the latency period is distinctively larger than the incubation period. In other cases, the effect of contact tracing can be decreased by super-spreaders. Numerical analysis with parameters suited for SARS-CoV-2 indicates that super-spreaders do not decrease the effect of contact tracing crucially in case of that infection.
Collapse
Affiliation(s)
- Johannes Müller
- Center for Mathematics, Technische Universität München, 85748, Garching, Germany. .,Institute for Computational Biology, Helmholtz Center Munich, 85764, Neuherberg, Germany.
| | - Volker Hösel
- grid.6936.a0000000123222966Center for Mathematics, Technische Universität München, 85748 Garching, Germany
| |
Collapse
|
11
|
Favero M, Scalia Tomba G, Britton T. Modelling preventive measures and their effect on generation times in emerging epidemics. J R Soc Interface 2022; 19:20220128. [PMID: 35702865 PMCID: PMC9198515 DOI: 10.1098/rsif.2022.0128] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 05/12/2022] [Indexed: 12/21/2022] Open
Abstract
We present a stochastic epidemic model to study the effect of various preventive measures, such as uniform reduction of contacts and transmission, vaccination, isolation, screening and contact tracing, on a disease outbreak in a homogeneously mixing community. The model is based on an infectivity process, which we define through stochastic contact and infectiousness processes, so that each individual has an independent infectivity profile. In particular, we monitor variations of the reproduction number and of the distribution of generation times. We show that some interventions, i.e. uniform reduction and vaccination, affect the former while leaving the latter unchanged, whereas other interventions, i.e. isolation, screening and contact tracing, affect both quantities. We provide a theoretical analysis of the variation of these quantities, and we show that, in practice, the variation of the generation time distribution can be significant and that it can cause biases in the estimation of reproduction numbers. The framework, because of its general nature, captures the properties of many infectious diseases, but particular emphasis is on COVID-19, for which numerical results are provided.
Collapse
Affiliation(s)
- Martina Favero
- Department of Mathematics, Stockholm University, Stockholm, Sweden
| | | | - Tom Britton
- Department of Mathematics, Stockholm University, Stockholm, Sweden
| |
Collapse
|
12
|
Biala TA, Afolabi YO, Khaliq AQM. How efficient is contact tracing in mitigating the spread of COVID-19? a mathematical modeling approach. APPLIED MATHEMATICAL MODELLING 2022; 103:714-730. [PMID: 34815616 PMCID: PMC8603240 DOI: 10.1016/j.apm.2021.11.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2020] [Revised: 10/24/2021] [Accepted: 11/07/2021] [Indexed: 05/26/2023]
Abstract
Contact Tracing (CT) is one of the measures taken by government and health officials to reduce the spread of the novel coronavirus. In this paper, we investigate its efficacy by developing a compartmental model for assessing its impact on mitigating the spread of the virus. We describe the impact on the reproduction number R 0 of COVID-19. In particular, we discuss the importance and relevance of parameters of the model such as the number of reported cases, effectiveness of tracking and monitoring policy, and the transmission rates to contact tracing. We describe the terms "perfect tracking", "perfect monitoring" and "perfect reporting" to indicate that traced contacts will be tracked while incubating, tracked contacts are efficiently monitored so that they do not cause secondary infections, and all infected persons are reported, respectively. We consider three special scenarios: (1) perfect monitoring and perfect tracking of contacts of a reported case, (2) perfect reporting of cases and perfect monitoring of tracked reported cases and (3) perfect reporting and perfect tracking of contacts of reported cases. Furthermore, we gave a lower bound on the proportion of contacts to be traced to ensure that the effective reproduction, R c , is below one and describe R c in terms of observable quantities such as the proportion of reported and traced cases. Model simulations using the COVID-19 data obtained from John Hopkins University for some selected states in the US suggest that even late intervention of CT may reasonably reduce the transmission of COVID-19 and reduce peak hospitalizations and deaths. In particular, our findings suggest that effective monitoring policy of tracked cases and tracking of traced contacts while incubating are more crucial than tracing more contacts. The use of CT coupled with other measures such as social distancing, use of face mask, self-isolation or quarantine and lockdowns will greatly reduce the spread of the epidemic as well as peak hospitalizations and total deaths.
Collapse
Affiliation(s)
- T A Biala
- Department of Mathematics, The Ohio State University, USA
| | - Y O Afolabi
- Department of Mathematics, University of Louisiana at Lafayette, USA
| | - A Q M Khaliq
- Department of Mathematical Sciences, Middle Tennessee State University, USA
| |
Collapse
|
13
|
Garousi V, Cutting D, Felderer M. Mining user reviews of COVID contact-tracing apps: An exploratory analysis of nine European apps. THE JOURNAL OF SYSTEMS AND SOFTWARE 2022; 184:111136. [PMID: 34751198 PMCID: PMC8566091 DOI: 10.1016/j.jss.2021.111136] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 06/06/2021] [Accepted: 10/25/2021] [Indexed: 05/16/2023]
Abstract
CONTEXT More than 78 countries have developed COVID contact-tracing apps to limit the spread of coronavirus. However, many experts and scientists cast doubt on the effectiveness of those apps. For each app, a large number of reviews have been entered by end-users in app stores. OBJECTIVE Our goal is to gain insights into the user reviews of those apps, and to find out the main problems that users have reported. Our focus is to assess the "software in society" aspects of the apps, based on user reviews. METHOD We selected nine European national apps for our analysis and used a commercial app-review analytics tool to extract and mine the user reviews. For all the apps combined, our dataset includes 39,425 user reviews. RESULTS Results show that users are generally dissatisfied with the nine apps under study, except the Scottish ("Protect Scotland") app. Some of the major issues that users have complained about are high battery drainage and doubts on whether apps are really working. CONCLUSION Our results show that more work is needed by the stakeholders behind the apps (e.g., app developers, decision-makers, public health experts) to improve the public adoption, software quality and public perception of these apps.
Collapse
Affiliation(s)
- Vahid Garousi
- Queen's University Belfast, UK
- Bahar Software Engineering Consulting Corporation, UK
| | | | - Michael Felderer
- University of Innsbruck, Austria
- Blekinge Institute of Technology, Sweden
| |
Collapse
|
14
|
Prieto K. Current forecast of COVID-19 in Mexico: A Bayesian and machine learning approaches. PLoS One 2022; 17:e0259958. [PMID: 35061688 PMCID: PMC8782335 DOI: 10.1371/journal.pone.0259958] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Accepted: 10/29/2021] [Indexed: 12/24/2022] Open
Abstract
The COVID-19 pandemic has been widely spread and affected millions of people and caused hundreds of deaths worldwide, especially in patients with comorbilities and COVID-19. This manuscript aims to present models to predict, firstly, the number of coronavirus cases and secondly, the hospital care demand and mortality based on COVID-19 patients who have been diagnosed with other diseases. For the first part, I present a projection of the spread of coronavirus in Mexico, which is based on a contact tracing model using Bayesian inference. I investigate the health profile of individuals diagnosed with coronavirus to predict their type of patient care (inpatient or outpatient) and survival. Specifically, I analyze the comorbidity associated with coronavirus using Machine Learning. I have implemented two classifiers: I use the first classifier to predict the type of care procedure that a person diagnosed with coronavirus presenting chronic diseases will obtain (i.e. outpatient or hospitalised), in this way I estimate the hospital care demand; I use the second classifier to predict the survival or mortality of the patient (i.e. survived or deceased). I present two techniques to deal with these kinds of unbalanced datasets related to outpatient/hospitalised and survived/deceased cases (which occur in general for these types of coronavirus datasets) to obtain a better performance for the classification.
Collapse
Affiliation(s)
- Kernel Prieto
- Instituto de Matemáticas, Universidad Nacional Autónoma de México, Mexico City, México
| |
Collapse
|
15
|
Browne CJ, Gulbudak H, Macdonald JC. Differential impacts of contact tracing and lockdowns on outbreak size in COVID-19 model applied to China. J Theor Biol 2022; 532:110919. [PMID: 34592263 PMCID: PMC8474798 DOI: 10.1016/j.jtbi.2021.110919] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 09/20/2021] [Accepted: 09/22/2021] [Indexed: 02/07/2023]
Abstract
The COVID-19 pandemic has led to widespread attention given to the notions of "flattening the curve" during lockdowns, and successful contact tracing programs suppressing outbreaks. However a more nuanced picture of these interventions' effects on epidemic trajectories is necessary. By mathematical modeling each as reactive quarantine measures, dependent on current infection rates, with different mechanisms of action, we analytically derive distinct nonlinear effects of these interventions on final and peak outbreak size. We simultaneously fit the model to provincial reported case and aggregated quarantined contact data from China. Lockdowns compressed the outbreak in China inversely proportional to population quarantine rates, revealing their critical dependence on timing. Contact tracing had significantly less impact on final outbreak size, but did lead to peak size reduction. Our analysis suggests that altering the cumulative cases in a rapidly spreading outbreak requires sustained interventions that decrease the reproduction number close to one, otherwise some type of swift lockdown measure may be needed.
Collapse
Affiliation(s)
- Cameron J Browne
- Department of Mathematics, University of Louisiana at Lafayette, United States.
| | - Hayriye Gulbudak
- Department of Mathematics, University of Louisiana at Lafayette, United States
| | - Joshua C Macdonald
- Department of Mathematics, University of Louisiana at Lafayette, United States
| |
Collapse
|
16
|
Gulbudak H, Qu Z, Milner F, Tuncer N. Sensitivity Analysis in an Immuno-Epidemiological Vector-Host Model. Bull Math Biol 2022; 84:27. [PMID: 34982249 PMCID: PMC8724773 DOI: 10.1007/s11538-021-00979-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 11/23/2021] [Indexed: 11/30/2022]
Abstract
Sensitivity Analysis (SA) is a useful tool to measure the impact of changes in model parameters on the infection dynamics, particularly to quantify the expected efficacy of disease control strategies. SA has only been applied to epidemic models at the population level, ignoring the effect of within-host virus-with-immune-system interactions on the disease spread. Connecting the scales from individual to population can help inform drug and vaccine development. Thus the value of understanding the impact of immunological parameters on epidemiological quantities. Here we consider an age-since-infection structured vector-host model, in which epidemiological parameters are formulated as functions of within-host virus and antibody densities, governed by an ODE system. We then use SA for these immuno-epidemiological models to investigate the impact of immunological parameters on population-level disease dynamics such as basic reproduction number, final size of the epidemic or the infectiousness at different phases of an outbreak. As a case study, we consider Rift Valley Fever Disease utilizing parameter estimations from prior studies. SA indicates that \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$1\%$$\end{document}1% increase in within-host pathogen growth rate can lead up to \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$8\%$$\end{document}8% increase in \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$\mathcal R_0,$$\end{document}R0, up to \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$1 \%$$\end{document}1% increase in steady-state infected host abundance, and up to \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$4\%$$\end{document}4% increase in infectiousness of hosts when the reproduction number \documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$\mathcal R_0$$\end{document}R0 is larger than one. These significant increases in population-scale disease quantities suggest that control strategies that reduce the within-host pathogen growth can be important in reducing disease prevalence.
Collapse
Affiliation(s)
- Hayriye Gulbudak
- Department of Mathematics, University of Louisiana at Lafayette, 217 Maxim Doucet Hall, Lafayette, LA, P.O. Box 43568, USA.
| | - Zhuolin Qu
- Department of Mathematics, University of Texas at San Antonio, One UTSA Circle, San Antonio, TX, 78249, USA
| | - Fabio Milner
- School of Mathematical and Statistical Sciences, Arizona State University, 825 Wexler Hall, P.O. Box 871804, Tempe, AZ, 85287, USA
| | - Necibe Tuncer
- Department of Mathematical Sciences, Florida Atlantic University, Science Building, Room 234 777 Glades Road, Boca Raton, FL, 33431, USA
| |
Collapse
|
17
|
McAloon CG, Wall P, Butler F, Codd M, Gormley E, Walsh C, Duggan J, Murphy TB, Nolan P, Smyth B, O'Brien K, Teljeur C, Green MJ, O'Grady L, Culhane K, Buckley C, Carroll C, Doyle S, Martin J, More SJ. Numbers of close contacts of individuals infected with SARS-CoV-2 and their association with government intervention strategies. BMC Public Health 2021; 21:2238. [PMID: 34886842 PMCID: PMC8655330 DOI: 10.1186/s12889-021-12318-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 11/22/2021] [Indexed: 12/23/2022] Open
Abstract
Background Contact tracing is conducted with the primary purpose of interrupting transmission from individuals who are likely to be infectious to others. Secondary analyses of data on the numbers of close contacts of confirmed cases could also: provide an early signal of increases in contact patterns that might precede larger than expected case numbers; evaluate the impact of government interventions on the number of contacts of confirmed cases; or provide data information on contact rates between age cohorts for the purpose of epidemiological modelling. We analysed data from 140,204 close contacts of 39,861 cases in Ireland from 1st May to 1st December 2020. Results Negative binomial regression models highlighted greater numbers of contacts within specific population demographics, after correcting for temporal associations. Separate segmented regression models of the number of cases over time and the average number of contacts per case indicated that a breakpoint indicating a rapid decrease in the number of contacts per case in October 2020 preceded a breakpoint indicating a reduction in the number of cases by 11 days. Conclusions We found that the number of contacts per infected case was overdispersed, the mean varied considerable over time and was temporally associated with government interventions. Analysis of the reported number of contacts per individual in contact tracing data may be a useful early indicator of changes in behaviour in response to, or indeed despite, government restrictions. This study provides useful information for triangulating assumptions regarding the contact mixing rates between different age cohorts for epidemiological modelling. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-021-12318-y.
Collapse
Affiliation(s)
- Conor G McAloon
- School of Veterinary Medicine, University College Dublin, Belfield, Dublin 4, Ireland.
| | - Patrick Wall
- School of Public Health, Physiotherapy and Sports Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Francis Butler
- School of Biosystems and Food Engineering, University College Dublin, Belfield, Dublin 4, Ireland
| | - Mary Codd
- School of Public Health, Physiotherapy and Sports Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Eamonn Gormley
- School of Veterinary Medicine, University College Dublin, Belfield, Dublin 4, Ireland
| | - Cathal Walsh
- Department of Mathematics and Statistics, University of Limerick, Limerick, Ireland
| | - Jim Duggan
- School of Computer Science, National University of Ireland Galway, Galway, Ireland
| | - T Brendan Murphy
- School of Mathematics and Statistics, University College Dublin, Belfield, Dublin 4, Ireland
| | - Philip Nolan
- National University of Ireland Maynooth, Kildare, Ireland
| | - Breda Smyth
- Department of Public Health, Health Service Executive West, Galway, Ireland
| | | | - Conor Teljeur
- Health Information and Quality Authority, George's Court, Dublin 7, Ireland
| | - Martin J Green
- School of Veterinary Medicine and Science, University of Nottingham, Nottingham, UK
| | - Luke O'Grady
- School of Veterinary Medicine, University College Dublin, Belfield, Dublin 4, Ireland.,School of Veterinary Medicine and Science, University of Nottingham, Nottingham, UK
| | - Kieran Culhane
- Central Statistics Office, Ardee road, Rathmines, Dublin, Ireland
| | - Claire Buckley
- COVID-19 Contact Management Programme, Health Service Executive, Dublin, Ireland
| | - Ciara Carroll
- COVID-19 Contact Management Programme, Health Service Executive, Dublin, Ireland
| | - Sarah Doyle
- COVID-19 Contact Management Programme, Health Service Executive, Dublin, Ireland
| | - Jennifer Martin
- COVID-19 Contact Management Programme, Health Service Executive, Dublin, Ireland
| | - Simon J More
- School of Veterinary Medicine, University College Dublin, Belfield, Dublin 4, Ireland.,Centre for Veterinary Epidemiology and Risk Analysis, School of Veterinary Medicine, University College Dublin, Belfield, Dublin, Ireland
| |
Collapse
|
18
|
Evaluating the sensitivity of SARS-CoV-2 infection rates on college campuses to wastewater surveillance. Infect Dis Model 2021; 6:1144-1158. [PMID: 34568643 PMCID: PMC8452452 DOI: 10.1016/j.idm.2021.09.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 09/14/2021] [Accepted: 09/14/2021] [Indexed: 11/21/2022] Open
Abstract
As college campuses reopened in fall 2020, we saw a large-scale experiment unfold on the efficacy of various strategies to contain the SARS-CoV-2 virus. Traditional individual surveillance testing via nasal swabs and/or saliva is among the measures that colleges are pursuing to reduce the spread of the virus on campus. Additionally, some colleges are testing wastewater on their campuses for signs of infection, which can provide an early warning signal for campuses to locate COVID-positive individuals. However, a representation of wastewater surveillance has not yet been incorporated into epidemiological models for college campuses, nor has the efficacy of wastewater screening been evaluated relative to traditional individual surveillance testing, within the structure of these models. Here, we implement a new model component for wastewater surveillance within an established epidemiological model for college campuses. We use a hypothetical residential university to evaluate the efficacy of wastewater surveillance for maintaining low infection rates. We find that wastewater sampling with a 1-day lag to initiate individual screening tests, plus completing the subsequent tests within a 4-day period can keep overall infections within 5% of the infection rates seen with traditional individual surveillance testing. Our results also indicate that wastewater surveillance can effectively reduce the number of false positive cases by identifying subpopulations for surveillance testing where infectious individuals are more likely to be found. Through a Monte Carlo risk analysis, we find that surveillance testing that relies solely on wastewater sampling can be fragile against scenarios with high viral reproductive numbers and high rates of infection of campus community members by outside sources. These results point to the practical importance of additional surveillance measures to limit the spread of the virus on campus and the necessity of a proactive response to the initial signs of outbreak.
Collapse
|
19
|
Kolumbus Y, Nisan N. On the effectiveness of tracking and testing in SEIR models for improving health vs. economy trade-offs. Sci Rep 2021; 11:16305. [PMID: 34381096 PMCID: PMC8357840 DOI: 10.1038/s41598-021-95415-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Accepted: 07/22/2021] [Indexed: 11/16/2022] Open
Abstract
We study the effectiveness of tracking and testing policies for suppressing epidemic outbreaks. We evaluate the performance of tracking-based intervention methods on a network SEIR model, which we augment with an additional parameter to model pre-symptomatic and asymptomatic individuals, and study the effectiveness of these methods in combination with or as an alternative to quarantine and global lockdown policies. Our focus is on the basic trade-off between human-lives lost and economic costs, and on how this trade-off changes under different quarantine, lockdown, tracking, and testing policies. Our main findings are as follows: (1) Tests combined with patient quarantines reduce both economic costs and mortality, however, an extensive-scale testing capacity is required to achieve a significant improvement. (2) Tracking significantly reduces both economic costs and mortality. (3) Tracking combined with a moderate testing capacity can achieve containment without lockdowns. (4) In the presence of a flow of new incoming infections, dynamic "On-Off" lockdowns are more efficient than fixed lockdowns. In this setting as well, tracking strictly improves efficiency. The results show the extreme usefulness of policies that combine tracking and testing for reducing mortality and economic costs, and their potential to contain outbreaks without imposing any social distancing restrictions. This highlights the difficult social question of trading-off these gains against patient privacy, which is inevitably infringed by tracking.
Collapse
Affiliation(s)
- Yoav Kolumbus
- The Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel.
| | - Noam Nisan
- The Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
| |
Collapse
|
20
|
Pollmann TR, Schönert S, Müller J, Pollmann J, Resconi E, Wiesinger C, Haack C, Shtembari L, Turcati A, Neumair B, Meighen-Berger S, Zattera G, Neumair M, Apel U, Okolie A. The impact of digital contact tracing on the SARS-CoV-2 pandemic-a comprehensive modelling study. EPJ DATA SCIENCE 2021; 10:37. [PMID: 34306910 PMCID: PMC8290404 DOI: 10.1140/epjds/s13688-021-00290-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 06/22/2021] [Indexed: 05/08/2023]
Abstract
Contact tracing is one of several strategies employed in many countries to curb the spread of SARS-CoV-2. Digital contact tracing (DCT) uses tools such as cell-phone applications to improve tracing speed and reach. We model the impact of DCT on the spread of the virus for a large epidemiological parameter space consistent with current literature on SARS-CoV-2. We also model DCT in combination with random testing (RT) and social distancing (SD). Modelling is done with two independently developed individual-based (stochastic) models that use the Monte Carlo technique, benchmarked against each other and against two types of deterministic models. For current best estimates of the number of asymptomatic SARS-CoV-2 carriers (approximately 40%), their contagiousness (similar to that of symptomatic carriers), the reproductive number before interventions ( R 0 at least 3) we find that DCT must be combined with other interventions such as SD and/or RT to push the reproductive number below one. At least 60% of the population would have to use the DCT system for its effect to become significant. On its own, DCT cannot bring the reproductive number below 1 unless nearly the entire population uses the DCT system and follows quarantining and testing protocols strictly. For lower uptake of the DCT system, DCT still reduces the number of people that become infected. When DCT is deployed in a population with an ongoing outbreak where O (0.1%) of the population have already been infected, the gains of the DCT intervention come at the cost of requiring up to 15% of the population to be quarantined (in response to being traced) on average each day for the duration of the epidemic, even when there is sufficient testing capability to test every traced person.
Collapse
Affiliation(s)
- Tina R. Pollmann
- Physics Department, Technical University of Munich, 85748 Garching, Germany
| | - Stefan Schönert
- Physics Department, Technical University of Munich, 85748 Garching, Germany
| | - Johannes Müller
- Center for Mathematical Sciences, Technical University of Munich, 85748 Garching, Germany
- Institute for Computational Biology, Helmholtz Center Munich, 85764 Neuherberg, Germany
| | - Julia Pollmann
- Department of Medical Oncology, University Hospital Heidelberg, National Center for Tumor Diseases (NCT) Heidelberg, 69120 Heidelberg, Germany
| | - Elisa Resconi
- Physics Department, Technical University of Munich, 85748 Garching, Germany
| | | | - Christian Haack
- Physics Department, Technical University of Munich, 85748 Garching, Germany
| | | | - Andrea Turcati
- Physics Department, Technical University of Munich, 85748 Garching, Germany
| | - Birgit Neumair
- Physics Department, Technical University of Munich, 85748 Garching, Germany
| | | | - Giovanni Zattera
- Physics Department, Technical University of Munich, 85748 Garching, Germany
| | - Matthias Neumair
- Department of Mathematics, Technical University of Munich, 85748 Garching, Germany
| | - Uljana Apel
- Center for Mathematical Sciences, Technical University of Munich, 85748 Garching, Germany
| | - Augustine Okolie
- Center for Mathematical Sciences, Technical University of Munich, 85748 Garching, Germany
| |
Collapse
|
21
|
Hogan K, Macedo B, Macha V, Barman A, Jiang X. Contact Tracing Apps: Lessons Learned on Privacy, Autonomy, and the Need for Detailed and Thoughtful Implementation. JMIR Med Inform 2021; 9:e27449. [PMID: 34254937 PMCID: PMC8291141 DOI: 10.2196/27449] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 04/03/2021] [Accepted: 04/14/2021] [Indexed: 02/06/2023] Open
Abstract
The global and national response to the COVID-19 pandemic has been inadequate due to a collective lack of preparation and a shortage of available tools for responding to a large-scale pandemic. By applying lessons learned to create better preventative methods and speedier interventions, the harm of a future pandemic may be dramatically reduced. One potential measure is the widespread use of contact tracing apps. While such apps were designed to combat the COVID-19 pandemic, the time scale in which these apps were deployed proved a significant barrier to efficacy. Many companies and governments sprinted to deploy contact tracing apps that were not properly vetted for performance, privacy, or security issues. The hasty development of incomplete contact tracing apps undermined public trust and negatively influenced perceptions of app efficacy. As a result, many of these apps had poor voluntary public uptake, which greatly decreased the apps' efficacy. Now, with lessons learned from this pandemic, groups can better design and test apps in preparation for the future. In this viewpoint, we outline common strategies employed for contact tracing apps, detail the successes and shortcomings of several prominent apps, and describe lessons learned that may be used to shape effective contact tracing apps for the present and future. Future app designers can keep these lessons in mind to create a version that is suitable for their local culture, especially with regard to local attitudes toward privacy-utility tradeoffs during public health crises.
Collapse
Affiliation(s)
- Katie Hogan
- Department of Bioengineering, Rice University, Houston, TX, United States
| | - Briana Macedo
- School of Engineering, Princeton University, Princeton, NJ, United States
| | - Venkata Macha
- School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Arko Barman
- Department of Electrical & Computer Engineering, Rice University, Houston, TX, United States
- Data to Knowledge Lab, Rice University, Houston, TX, United States
| | - Xiaoqian Jiang
- School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, United States
| |
Collapse
|
22
|
Varghese A, Kolamban S, Sherimon V, Lacap EM, Ahmed SS, Sreedhar JP, Al Harthi H, Al Shuaily HS. SEAMHCRD deterministic compartmental model based on clinical stages of infection for COVID-19 pandemic in Sultanate of Oman. Sci Rep 2021; 11:11984. [PMID: 34099741 PMCID: PMC8184795 DOI: 10.1038/s41598-021-91114-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 05/10/2021] [Indexed: 01/22/2023] Open
Abstract
The present novel coronavirus (COVID-19) infection has engendered a worldwide crisis on an enormous scale within a very short period. The effective solution for this pandemic is to recognize the nature and spread of the disease so that appropriate policies can be framed. Mathematical modelling is always at the forefront to understand and provide an adequate description of the transmission of any disease. In this research work, we have formulated a deterministic compartmental model (SEAMHCRD) including various stages of infection, such as Mild, Moderate, Severe and Critical to study the spreading of COVID-19 and estimated the model parameters by fitting the model with the reported data of ongoing pandemic in Oman. The steady-state, stability and final pandemic size of the model has been proved mathematically. The various transmission as well as transition parameters are estimated during the period from June 4th to July 30th, 2020. Based on the currently estimated parameters, the pandemic size is also predicted for another 100 days. Sensitivity analysis is performed to identify the key model parameters, and the parameter gamma due to contact with the symptomatic moderately infected is found to be more significant in spreading the disease. Accordingly, the corresponding basic reproduction number has also been computed using the Next Generation Matrix (NGM) method. As the value of the basic reproduction number (R0) is 0.9761 during the period from June 4th to July 30th, 2020, the disease-free equilibrium is stable. Isolation and tracing the contact of infected individuals are recommended to control the spread of disease.
Collapse
Affiliation(s)
- Abraham Varghese
- Department of Information Technology, Faculty of Mathematics, University of Technology and Applied Sciences, Muscat, Sultanate of Oman
| | - Shajidmon Kolamban
- Department of Information Technology, Faculty of Mathematics, University of Technology and Applied Sciences, Muscat, Sultanate of Oman
| | - Vinu Sherimon
- Department of Information Technology, Faculty of IT, University of Technology and Applied Sciences, Muscat, Sultanate of Oman.
| | - Eduardo M Lacap
- Department of Information Technology, Faculty of Statistics, University of Technology and Applied Sciences, Muscat, Sultanate of Oman
| | - Saad Salman Ahmed
- Department of Information Technology, Faculty of Mathematics, University of Technology and Applied Sciences, Muscat, Sultanate of Oman
| | - Jagath Prasad Sreedhar
- Department of Information Technology, Faculty of Statistics, University of Technology and Applied Sciences, Muscat, Sultanate of Oman
| | | | - Huda Salim Al Shuaily
- Department of Information Technology, Faculty of IT, University of Technology and Applied Sciences, Muscat, Sultanate of Oman
| |
Collapse
|
23
|
A Mathematical Model of Contact Tracing during the 2014–2016 West African Ebola Outbreak. MATHEMATICS 2021. [DOI: 10.3390/math9060608] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The 2014–2016 West African outbreak of Ebola Virus Disease (EVD) was the largest and most deadly to date. Contact tracing, following up those who may have been infected through contact with an infected individual to prevent secondary spread, plays a vital role in controlling such outbreaks. Our aim in this work was to mechanistically represent the contact tracing process to illustrate potential areas of improvement in managing contact tracing efforts. We also explored the role contact tracing played in eventually ending the outbreak. We present a system of ordinary differential equations to model contact tracing in Sierra Leonne during the outbreak. Using data on cumulative cases and deaths, we estimate most of the parameters in our model. We include the novel features of counting the total number of people being traced and tying this directly to the number of tracers doing this work. Our work highlights the importance of incorporating changing behavior into one’s model as needed when indicated by the data and reported trends. Our results show that a larger contact tracing program would have reduced the death toll of the outbreak. Counting the total number of people being traced and including changes in behavior in our model led to better understanding of disease management.
Collapse
|
24
|
Sturniolo S, Waites W, Colbourn T, Manheim D, Panovska-Griffiths J. Testing, tracing and isolation in compartmental models. PLoS Comput Biol 2021; 17:e1008633. [PMID: 33661888 PMCID: PMC7932151 DOI: 10.1371/journal.pcbi.1008633] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Accepted: 12/14/2020] [Indexed: 01/12/2023] Open
Abstract
Existing compartmental mathematical modelling methods for epidemics, such as SEIR models, cannot accurately represent effects of contact tracing. This makes them inappropriate for evaluating testing and contact tracing strategies to contain an outbreak. An alternative used in practice is the application of agent- or individual-based models (ABM). However ABMs are complex, less well-understood and much more computationally expensive. This paper presents a new method for accurately including the effects of Testing, contact-Tracing and Isolation (TTI) strategies in standard compartmental models. We derive our method using a careful probabilistic argument to show how contact tracing at the individual level is reflected in aggregate on the population level. We show that the resultant SEIR-TTI model accurately approximates the behaviour of a mechanistic agent-based model at far less computational cost. The computational efficiency is such that it can be easily and cheaply used for exploratory modelling to quantify the required levels of testing and tracing, alone and with other interventions, to assist adaptive planning for managing disease outbreaks.
Collapse
Affiliation(s)
- Simone Sturniolo
- Scientific Computing Department, UKRI, Rutherford Appleton Laboratory, Harwell, United Kingdom
| | - William Waites
- School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Tim Colbourn
- UCL Institute for Global Health, London, United Kingdom
| | - David Manheim
- University of Haifa Health and Risk Communication Research Center, Haifa, Israel
| | - Jasmina Panovska-Griffiths
- UCL Institute for Global Health, London, United Kingdom
- Department of Applied Health Research, UCL, London, United Kingdom
- Wolfson Centre for Mathematical Biology and The Queen’s College, Oxford University, Oxford, United Kingdom
| |
Collapse
|
25
|
Kim H, Paul A. Automated contact tracing: a game of big numbers in the time of COVID-19. J R Soc Interface 2021; 18:20200954. [PMID: 33622147 PMCID: PMC8086867 DOI: 10.1098/rsif.2020.0954] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Accepted: 02/01/2021] [Indexed: 12/19/2022] Open
Abstract
One of the more widely advocated solutions for slowing down the spread of COVID-19 has been automated contact tracing. Since proximity data can be collected by personal mobile devices, the natural proposal has been to use this for automated contact tracing providing a major gain over a manual implementation. In this work, we study the characteristics of voluntary and automated contact tracing and its effectiveness for mapping the spread of a pandemic due to the spread of SARS-CoV-2. We highlight the infrastructure and social structures required for automated contact tracing to work. We display the vulnerabilities of the strategy to inadequate sampling of the population, which results in the inability to sufficiently determine significant contact with infected individuals. Of crucial importance will be the participation of a significant fraction of the population for which we derive a minimum threshold. We conclude that relying largely on automated contact tracing without population-wide participation to contain the spread of the SARS-CoV-2 pandemic can be counterproductive and allow the pandemic to spread unchecked. The simultaneous implementation of various mitigation methods along with automated contact tracing is necessary for reaching an optimal solution to contain the pandemic.
Collapse
Affiliation(s)
- Hyunju Kim
- Beyond Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ, USA
- School of Earth and Space Exploration, Arizona State University, Tempe, AZ, USA
- ASU-SFI Center for Biosocial Complex Systems, Arizona State University and Santa Fe Institute, Tempe, AZ, USA
| | - Ayan Paul
- DESY, Notkestraße 85, 22607 Hamburg, Germany
- Institut für Physik, Humboldt-Universität zu Berlin, 12489 Berlin, Germany
| |
Collapse
|
26
|
Pollmann TR, Schönert S, Müller J, Pollmann J, Resconi E, Wiesinger C, Haack C, Shtembari L, Turcati A, Neumair B, Meighen-Berger S, Zattera G, Neumair M, Apel U, Okolie A. The impact of digital contact tracing on the SARS-CoV-2 pandemic-a comprehensive modelling study. EPJ DATA SCIENCE 2021; 10:37. [PMID: 34306910 DOI: 10.1101/2020.09.13.20192682v1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 06/22/2021] [Indexed: 05/20/2023]
Abstract
Contact tracing is one of several strategies employed in many countries to curb the spread of SARS-CoV-2. Digital contact tracing (DCT) uses tools such as cell-phone applications to improve tracing speed and reach. We model the impact of DCT on the spread of the virus for a large epidemiological parameter space consistent with current literature on SARS-CoV-2. We also model DCT in combination with random testing (RT) and social distancing (SD). Modelling is done with two independently developed individual-based (stochastic) models that use the Monte Carlo technique, benchmarked against each other and against two types of deterministic models. For current best estimates of the number of asymptomatic SARS-CoV-2 carriers (approximately 40%), their contagiousness (similar to that of symptomatic carriers), the reproductive number before interventions ( R 0 at least 3) we find that DCT must be combined with other interventions such as SD and/or RT to push the reproductive number below one. At least 60% of the population would have to use the DCT system for its effect to become significant. On its own, DCT cannot bring the reproductive number below 1 unless nearly the entire population uses the DCT system and follows quarantining and testing protocols strictly. For lower uptake of the DCT system, DCT still reduces the number of people that become infected. When DCT is deployed in a population with an ongoing outbreak where O (0.1%) of the population have already been infected, the gains of the DCT intervention come at the cost of requiring up to 15% of the population to be quarantined (in response to being traced) on average each day for the duration of the epidemic, even when there is sufficient testing capability to test every traced person.
Collapse
Affiliation(s)
- Tina R Pollmann
- Physics Department, Technical University of Munich, 85748 Garching, Germany
| | - Stefan Schönert
- Physics Department, Technical University of Munich, 85748 Garching, Germany
| | - Johannes Müller
- Center for Mathematical Sciences, Technical University of Munich, 85748 Garching, Germany
- Institute for Computational Biology, Helmholtz Center Munich, 85764 Neuherberg, Germany
| | - Julia Pollmann
- Department of Medical Oncology, University Hospital Heidelberg, National Center for Tumor Diseases (NCT) Heidelberg, 69120 Heidelberg, Germany
| | - Elisa Resconi
- Physics Department, Technical University of Munich, 85748 Garching, Germany
| | | | - Christian Haack
- Physics Department, Technical University of Munich, 85748 Garching, Germany
| | | | - Andrea Turcati
- Physics Department, Technical University of Munich, 85748 Garching, Germany
| | - Birgit Neumair
- Physics Department, Technical University of Munich, 85748 Garching, Germany
| | | | - Giovanni Zattera
- Physics Department, Technical University of Munich, 85748 Garching, Germany
| | - Matthias Neumair
- Department of Mathematics, Technical University of Munich, 85748 Garching, Germany
| | - Uljana Apel
- Center for Mathematical Sciences, Technical University of Munich, 85748 Garching, Germany
| | - Augustine Okolie
- Center for Mathematical Sciences, Technical University of Munich, 85748 Garching, Germany
| |
Collapse
|
27
|
Müller J, Kretzschmar M. Contact tracing - Old models and new challenges. Infect Dis Model 2020; 6:222-231. [PMID: 33506153 PMCID: PMC7806945 DOI: 10.1016/j.idm.2020.12.005] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2020] [Revised: 12/10/2020] [Accepted: 12/19/2020] [Indexed: 11/24/2022] Open
Abstract
Contact tracing is an effective method to control emerging infectious diseases. Since the 1980's, modellers are developing a consistent theory for contact tracing, with the aim to find effective and efficient implementations, and to assess the effects of contact tracing on the spread of an infectious disease. Despite the progress made in the area, there remain important open questions. In addition, technological developments, especially in the field of molecular biology (genetic sequencing of pathogens) and modern communication (digital contact tracing), have posed new challenges for the modelling community. In the present paper, we discuss modelling approaches for contact tracing and identify some of the current challenges for the field.
Collapse
Affiliation(s)
- Johannes Müller
- Mathematical Institute, Technical University of Munich, Boltzmannstr. 3, 85748, Garching, Germany
- Institute for Computational Biology, Helmholtz Center Munich, 85764, Neuherberg, Germany
| | - Mirjam Kretzschmar
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584CX, Utrecht, the Netherlands
| |
Collapse
|
28
|
Lunz D, Batt G, Ruess J. To quarantine, or not to quarantine: A theoretical framework for disease control via contact tracing. Epidemics 2020; 34:100428. [PMID: 33444928 PMCID: PMC7834522 DOI: 10.1016/j.epidem.2020.100428] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Revised: 11/10/2020] [Accepted: 12/08/2020] [Indexed: 01/17/2023] Open
Abstract
Contact tracing via smartphone applications is expected to be of major importance for maintaining control of the COVID-19 pandemic. However, viable deployment demands a minimal quarantine burden on the general public. That is, consideration must be given to unnecessary quarantining imposed by a contact tracing policy. Previous studies have modeled the role of contact tracing, but have not addressed how to balance these two competing needs. We propose a modeling framework that captures contact heterogeneity. This allows contact prioritization: contacts are only notified if they were acutely exposed to individuals who eventually tested positive. The framework thus allows us to address the delicate balance of preventing disease spread while minimizing the social and economic burdens of quarantine. This optimal contact tracing strategy is studied as a function of limitations in testing resources, partial technology adoption, and other intervention methods such as social distancing and lockdown measures. The framework is globally applicable, as the distribution describing contact heterogeneity is directly adaptable to any digital tracing implementation.
Collapse
Affiliation(s)
- Davin Lunz
- Inria Paris, 2 rue Simone Iff, 75012 Paris, France; Institut Pasteur, C3BI, 28 rue du Docteur-Roux, 75015 Paris, France; Inria Saclay - Île de France, 1 rue Honoré d'Estienne d'Orves, 91120 Palaiseau, France; École Polytechnique, CMAP, route de Saclay, 91128 Palaiseau, France.
| | - Gregory Batt
- Inria Paris, 2 rue Simone Iff, 75012 Paris, France; Institut Pasteur, C3BI, 28 rue du Docteur-Roux, 75015 Paris, France
| | - Jakob Ruess
- Inria Paris, 2 rue Simone Iff, 75012 Paris, France; Institut Pasteur, C3BI, 28 rue du Docteur-Roux, 75015 Paris, France
| |
Collapse
|
29
|
Abo SM, Smith? R. Modelling the daily risk of Ebola in the presence and absence of a potential vaccine. Infect Dis Model 2020; 5:905-917. [PMID: 33078134 PMCID: PMC7557810 DOI: 10.1016/j.idm.2020.10.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2020] [Revised: 10/04/2020] [Accepted: 10/05/2020] [Indexed: 11/23/2022] Open
Abstract
Ebola virus - one of the deadliest viral diseases, with a mortality rate around 90% - damages the immune system and organs, with symptoms including episodic fever, chills, malaise and myalgia. The Recombinant Vesicular Stomatitis Virus-based candidate vaccine (rVSV-ZEBOV) has demonstrated clinical efficacy against Ebola in ring-vaccination clinical trials. In order to evaluate the potential effect of this candidate vaccine, we developed risk equations for the daily risk of Ebola infection both currently and after vaccination. The risk equations account for the basic transmission probability of Ebola and the lowered risk due to various protection protocols: vaccination, hazmat suits, reduced contact with the infected living and dead bodies. Parameter space was sampled using Latin Hypercube Sampling, a statistical method for generating a near-random sample of parameter values. We found that at a high transmission rate of Ebola (i.e., if the transmission rate is greater than 90%), a large fraction of the population must be vaccinated (>80%) to achieve a 50% decrease in the daily risk of infection. If a vaccine is introduced, it must have at least 50% efficacy, and almost everyone in the affected areas must receive it to effectively control outbreaks of Ebola. These results indicate that a low-efficacy Ebola vaccine runs the risk of having vaccinated people be overconfident in a weak vaccine and hence the possibility that the vaccine could make the situation worse, unless the population can be sufficiently educated about the necessity for high vaccine uptake.
Collapse
Affiliation(s)
- Stéphanie M.C. Abo
- Department of Applied Mathematics, The University of Waterloo, Waterloo, Canada
| | - Robert Smith?
- Department of Mathematics and Faculty of Medicine, The University of Ottawa, 150 Louis-Pasteur Pvt, Ottawa, ON, K1N6N5, Canada
| |
Collapse
|
30
|
A microscopic approach to study the onset of a highly infectious disease spreading. Math Biosci 2020; 329:108475. [PMID: 32931776 DOI: 10.1016/j.mbs.2020.108475] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Revised: 07/23/2020] [Accepted: 08/30/2020] [Indexed: 11/23/2022]
Abstract
We combine a pedestrian dynamics model with a contact tracking method to simulate the initial spreading of a highly infectious airborne disease in a confined environment. We focus on a medium size population (up to 1000 people) with a small number of infectious people (1 or 2) and the rest of the people are divided between immune and susceptible. We adopt a space-continuous model that represents pedestrian dynamics by the forces acting on them, i.e. a microscopic force-based model. Once discretized, the model results in a high-dimensional system of second order ordinary differential equations. Before adding the contact tracking to the pedestrian dynamics model, we calibrate the model parameters, compare the model results against empirical data, and show that pedestrian self-organization into lanes can be captured. We consider an explicit approach for contact tracking by introducing a sickness domain around a sick person. A healthy but susceptible person who remains in the sickness domain for a certain amount of time may get infected (with a prescribed probability) and become a so-called secondary contact. As a concrete setting to simulate the onset of disease spreading, we consider terminals in two US airports: Hobby Airport in Houston and the Atlanta International Airport. We consider different scenarios and we quantify the increase in average number of secondary contacts as a given terminal becomes more densely populated, the percentage of immune people decreases, the number of primary contacts increases, and areas of high density (such as the boarding buses) are present.
Collapse
|
31
|
Afzal I, Abdul Raheem R, Rafeeq N, Moosa S. Contact Tracing for Containment of Novel Coronavirus Disease (COVID-19) in the Early Phase of the Epidemic in the Maldives. Asia Pac J Public Health 2020; 33:131-133. [PMID: 32864996 DOI: 10.1177/1010539520956447] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Affiliation(s)
| | | | | | - Sheena Moosa
- The Maldives National University, Malé, Maldives
| |
Collapse
|
32
|
Mahmood S, Hasan K, Colder Carras M, Labrique A. Global Preparedness Against COVID-19: We Must Leverage the Power of Digital Health. JMIR Public Health Surveill 2020; 6:e18980. [PMID: 32297868 PMCID: PMC7164944 DOI: 10.2196/18980] [Citation(s) in RCA: 112] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 04/08/2020] [Accepted: 04/09/2020] [Indexed: 12/20/2022] Open
Abstract
The coronavirus disease (COVID-19) pandemic has revealed many areas of public health preparedness that are lacking, especially in lower- and middle-income countries. Digital interventions provide many opportunities for strengthening health systems and could be vital resources in the current public health emergency. We provide several use cases for infection control, home-based diagnosis and screening, empowerment through information, public health surveillance and epidemiology, and leveraging crowd-sourced data. A thoughtful, concerted effort-leveraging existing experience and robust enterprise-grade technologies-can have a substantive impact on the immediate and distal consequences of COVID-19.
Collapse
Affiliation(s)
| | | | - Michelle Colder Carras
- International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Alain Labrique
- International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| |
Collapse
|
33
|
Yasaka TM, Lehrich BM, Sahyouni R. Peer-to-Peer Contact Tracing: Development of a Privacy-Preserving Smartphone App. JMIR Mhealth Uhealth 2020; 8:e18936. [PMID: 32240973 PMCID: PMC7144575 DOI: 10.2196/18936] [Citation(s) in RCA: 97] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 03/31/2020] [Accepted: 04/01/2020] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND The novel coronavirus disease 2019 (COVID-19) pandemic is an urgent public health crisis, with epidemiologic models predicting severe consequences, including high death rates, if the virus is permitted to run its course without any intervention or response. Contact tracing using smartphone technology is a powerful tool that may be employed to limit disease transmission during an epidemic or pandemic; yet, contact tracing apps present significant privacy concerns regarding the collection of personal data such as location. OBJECTIVE The aim of this study is to develop an effective contact tracing smartphone app that respects user privacy by not collecting location information or other personal data. METHODS We propose the use of an anonymized graph of interpersonal interactions to conduct a novel form of contact tracing and have developed a proof-of-concept smartphone app that implements this approach. Additionally, we developed a computer simulation model that demonstrates the impact of our proposal on epidemic or pandemic outbreak trajectories across multiple rates of adoption. RESULTS Our proof-of-concept smartphone app allows users to create "checkpoints" for contact tracing, check their risk level based on their past interactions, and anonymously self-report a positive status to their peer network. Our simulation results suggest that higher adoption rates of such an app may result in a better controlled epidemic or pandemic outbreak. CONCLUSIONS Our proposed smartphone-based contact tracing method presents a novel solution that preserves privacy while demonstrating the potential to suppress an epidemic or pandemic outbreak. This app could potentially be applied to the current COVID-19 pandemic as well as other epidemics or pandemics in the future to achieve a middle ground between drastic isolation measures and unmitigated disease spread.
Collapse
Affiliation(s)
- Tyler M Yasaka
- Department of Otolaryngology - Head and Neck Surgery, University of California, Irvine, Irvine, CA, United States
| | - Brandon M Lehrich
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States
| | - Ronald Sahyouni
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States.,Medical Scientist Training Program, University of California, Irvine, Irvine, CA, United States
| |
Collapse
|
34
|
Chang R, Wang H, Zhang S, Wang Z, Dong Y, Tsamlag L, Yu X, Xu C, Yu Y, Long R, Liu NN, Chu Q, Wang Y, Xu G, Shen T, Wang S, Deng X, Huang J, Zhang X, Wang H, Cai Y. Phase- and epidemic region-adjusted estimation of the number of coronavirus disease 2019 cases in China. Front Med 2020; 14:199-209. [PMID: 32279219 PMCID: PMC7148426 DOI: 10.1007/s11684-020-0768-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Accepted: 03/14/2020] [Indexed: 10/28/2022]
Abstract
The outbreak of the coronavirus disease 2019 was first reported in Wuhan in December 2019 and gradually spread to other areas in China. After implementation of prevention and control measures, the estimation of the epidemic trend is needed. A phase- and region-adjusted SEIR model was applied for modeling and predicting the number of cases in Wuhan, Hubei Province and regions outside Hubei Province in China. The estimated number of infections could reach its peak in late February 2020 in Wuhan and Hubei Province, which is 55 303-84 520 and 83 944-129 312, respectively, while the epidemic peaks in regions outside Hubei Province in China could appear on February 13, 2020 with the estimated 13 035-19 108 cases. According to the estimation, the outbreak would abate in March and April all over China. Current estimation provided evidence for planned work resumption under stringent prevention and control in China to further support the fight against the epidemic. Nevertheless, there is still possibility of the second outbreak brought by the work resumption and population migration, especially from Hubei Province and high intensity cities outside Hubei Province. Strict prevention and control measures still need to be considered in the regions with high intensity of epidemic and densely-populated cities.
Collapse
Affiliation(s)
- Ruijie Chang
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Huwen Wang
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Shuxian Zhang
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Zezhou Wang
- Department of Cancer Prevention, Shanghai Cancer Center, Fudan University, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200025, China
| | - Yinqiao Dong
- Department of Environmental and Occupational Health, School of Public Health, China Medical University, Shenyang, 110122, China
| | - Lhakpa Tsamlag
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xiaoyue Yu
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Chen Xu
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yuelin Yu
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Rusi Long
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Ning-Ning Liu
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Qiao Chu
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Ying Wang
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Gang Xu
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Tian Shen
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Suping Wang
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xiaobei Deng
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Jinyan Huang
- State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, National Research Center for Translational Medicine (Shanghai), Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xinxin Zhang
- Research Laboratory of Clinical Virology, National Research Center for Translational Medicine (Shanghai), Ruijin Hospital and Ruijin Hospital North Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Hui Wang
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Yong Cai
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| |
Collapse
|
35
|
A Note on Observation Processes in Epidemic Models. Bull Math Biol 2020; 82:37. [PMID: 32146583 DOI: 10.1007/s11538-020-00713-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Accepted: 02/24/2020] [Indexed: 10/24/2022]
Abstract
Many disease models focus on characterizing the underlying transmission mechanism but make simple, possibly naive assumptions about how infections are reported. In this note, we use a simple deterministic Susceptible-Infected-Removed (SIR) model to compare two common assumptions about disease incidence reports: Individuals can report their infection as soon as they become infected or as soon as they recover. We show that incorrect assumptions about the underlying observation processes can bias estimates of the basic reproduction number and lead to overly narrow confidence intervals.
Collapse
|
36
|
Chowell G, Tariq A, Kiskowski M. Vaccination strategies to control Ebola epidemics in the context of variable household inaccessibility levels. PLoS Negl Trop Dis 2019; 13:e0007814. [PMID: 31751337 PMCID: PMC6894888 DOI: 10.1371/journal.pntd.0007814] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Revised: 12/05/2019] [Accepted: 09/27/2019] [Indexed: 12/01/2022] Open
Abstract
Despite a very effective vaccine, active conflict and community distrust during the ongoing DRC Ebola epidemic are undermining control efforts, including a ring vaccination strategy that requires the prompt immunization of close contacts of infected individuals. However, in April 2019, it was reported 20% or more of close contacts cannot be reached or refuse vaccination, and it is predicted that the ring vaccination strategy would not be effective with such a high level of inaccessibility. The vaccination strategy is now incorporating a “third ring” community-level vaccination that targets members of communities even if they are not known contacts of Ebola cases. To assess the impact of vaccination strategies for controlling Ebola epidemics in the context of variable levels of community accessibility, we employed an individual-level stochastic transmission model that incorporates four sources of heterogeneity: a proportion of the population is inaccessible for contact tracing and vaccination due to lack of confidence in interventions or geographic inaccessibility, two levels of population mixing resembling household and community transmission, two types of vaccine doses with different time periods until immunity, and transmission rates that depend on spatial distance. Our results indicate that a ring vaccination strategy alone would not be effective for containing the epidemic in the context of significant delays to vaccinating contacts even for low levels of household inaccessibility and affirm the positive impact of a supplemental community vaccination strategy. Our key results are that as levels of inaccessibility increase, there is a qualitative change in the effectiveness of the vaccination strategy. For higher levels of vaccine access, the probability that the epidemic will end steadily increases over time, even if probabilities are lower than they would be otherwise with full community participation. For levels of vaccine access that are too low, however, the vaccination strategies are not expected to be successful in ending the epidemic even though they help lower incidence levels, which saves lives, and makes the epidemic easier to contain and reduces spread to other communities. This qualitative change occurs for both types of vaccination strategies: ring vaccination is effective for containing an outbreak until the levels of inaccessibility exceeds approximately 10% in the context of significant delays to vaccinating contacts, a combined ring and community vaccination strategy is effective until the levels of inaccessibility exceeds approximately 50%. More broadly, our results underscore the need to enhance community engagement to public health interventions in order to enhance the effectiveness of control interventions to ensure outbreak containment. In the context of the ongoing Ebola epidemic in DRC, active conflict and community distrust are undermining control efforts, including vaccination strategies. In this paper, we employed an individual-level stochastic structured transmission model to assess the impact of vaccination strategies on epidemic control in the context of variable levels of household inaccessibility. We found that a ring vaccination strategy of close contacts would not be effective for containing the epidemic in the context of significant delays to vaccinating contacts even for low levels of household inaccessibility and evaluate the impact of a supplemental community vaccination strategy. For lower levels of inaccessibility, the probability of epidemic containment increases over time. For higher levels of inaccessibility, even the combined ring and community vaccination strategies are not expected to contain the epidemic even though they help lower incidence levels, which saves lives, makes the epidemic easier to contain and reduces spread to other communities. We found that ring vaccination is effective for containing an outbreak until the levels of inaccessibility exceeds approximately 10%, a combined ring and community vaccination strategy is effective until the levels of inaccessibility exceeds approximately 50%. Our findings underscore the need to enhance community engagement to public health interventions.
Collapse
Affiliation(s)
- Gerardo Chowell
- Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, GA, United States of America
- Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD, United States of America
- * E-mail: (GC); (AT); (MK)
| | - Amna Tariq
- Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, GA, United States of America
- * E-mail: (GC); (AT); (MK)
| | - Maria Kiskowski
- Department of Mathematics and Statistics, University South Alabama, Mobile, AL, United States of America
- * E-mail: (GC); (AT); (MK)
| |
Collapse
|
37
|
Xie Z. Data Fitting and Scenario Analysis of Vaccination in the 2014 Ebola Outbreak in Liberia. Osong Public Health Res Perspect 2019; 10:187-201. [PMID: 31263668 PMCID: PMC6590876 DOI: 10.24171/j.phrp.2019.10.3.10] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
Objectives This study aimed to extend an epidemiological model (SEIHFR) to analyze epidemic trends, and evaluate intervention efficacy. Methods SEIHFR was modified to examine disease transmission dynamics after vaccination for the Ebola outbreak. Using existing data from Liberia, sensitivity analysis of various epidemic scenarios was used to inform the model structure, estimate the basic reproduction number ℜ0 and investigate how the vaccination could effectively change the course of the epidemic. Results If a randomized mass vaccination strategy was adopted, vaccines would be administered prophylactically or as early as possible (depending on the availability of vaccines). An effective vaccination rate threshold for Liberia was estimated as 48.74% among susceptible individuals. If a ring vaccination strategy was adopted to control the spread of the Ebola virus, vaccines would be given to reduce the transmission rate improving the tracing rate of the contact persons of an infected individual. Conclusion The extended SEIHFR model predicted the total number of infected cases, number of deaths, number of recoveries, and duration of outbreaks among others with different levels of interventions such as vaccination rate. This model may be used to better understand the spread of Ebola and develop strategies that may achieve a disease-free state.
Collapse
Affiliation(s)
- Zhifu Xie
- School of Mathematics and Natural Sciences, The University of Southern Mississippi, Hattiesburg, Mississippi, United States
| |
Collapse
|
38
|
Bempong NE, Ruiz De Castañeda R, Schütte S, Bolon I, Keiser O, Escher G, Flahault A. Precision Global Health - The case of Ebola: a scoping review. J Glob Health 2019; 9:010404. [PMID: 30701068 PMCID: PMC6344070 DOI: 10.7189/jogh.09.010404] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND The 2014-2016 Ebola outbreak across West Africa was devastating, acting not only as a wake-up call for the global health community, but also as a catalyst for innovative change and global action. Improved infectious disease monitoring is the stepping-stone toward better disease prevention and control efforts, and recent research has revealed the potential of digital technologies to transform the field of global health. This scoping review aimed to identify which digital technologies may improve disease prevention and control, with regard to the 2014-2016 Ebola outbreak in West Africa. METHODS A search was conducted on PubMed, EBSCOhost and Web of Science, with search dates ranging from 2013 (01/01/2013) - 2017 (13/06/2017). Data was extracted into a summative table and data synthesized through grouping digital technology domains, using narrative and graphical methods. FINDINGS The scoping review identified 82 full-text articles, and revealed big data (48%, n = 39) and modeling (26%, n = 21) technologies to be the most utilized within the Ebola outbreak. Digital technologies were mainly used for surveillance purposes (90%, n = 74), and key challenges were related to scalability and misinformation from social media platforms. INTERPRETATION Digital technologies demonstrated their potential during the Ebola outbreak through: more rapid diagnostics, more precise predictions and estimations, increased knowledge transfer, and raising situational awareness through mHealth and social media platforms such as Twitter and Weibo. However, better integration into both citizen and health professionals' communities is necessary to maximise the potential of digital technologies.
Collapse
Affiliation(s)
- Nefti-Eboni Bempong
- Institute of Global Health, Faculty of Medicine, University of Geneva, Switzerland
| | | | - Stefanie Schütte
- Centre Virchow-Villermé for Public Health Paris- Berlin, Descartes, Université Sorbonne Paris Cité, France
| | - Isabelle Bolon
- Institute of Global Health, Faculty of Medicine, University of Geneva, Switzerland
| | - Olivia Keiser
- Institute of Global Health, Faculty of Medicine, University of Geneva, Switzerland
| | - Gérard Escher
- Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
| | - Antoine Flahault
- Institute of Global Health, Faculty of Medicine, University of Geneva, Switzerland
- Centre Virchow-Villermé for Public Health Paris- Berlin, Descartes, Université Sorbonne Paris Cité, France
| |
Collapse
|
39
|
Ponce J, Zheng Y, Lin G, Feng Z. Assessing the effects of modeling the spectrum of clinical symptoms on the dynamics and control of Ebola. J Theor Biol 2019; 467:111-122. [PMID: 30735738 DOI: 10.1016/j.jtbi.2019.01.013] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2018] [Revised: 10/27/2018] [Accepted: 01/08/2019] [Indexed: 10/27/2022]
Abstract
Mathematical modelers have attempted to capture the dynamics of Ebola transmission and to evaluate the effectiveness of control measures, as well as to make predictions about ongoing outbreaks. Many of their models consider only infections with typical symptoms, but Ebola presents clinically in a more complicated way. Even the most common symptom, fever, is not experienced by 13% of patients. This suggests that infected individuals could be asymptomatic or have moderately symptomatic infections as reported during previous Ebola outbreaks. To account crudely for the spectrum of clinical symptoms that characterizes Ebola infection, we developed a model including moderate and severe symptoms. Our model captures the dynamics of the recent outbreak of Ebola in Liberia. Our estimate of the basic reproduction number is 1.83 (CI: 1.72, 1.86), consistent with the WHO response team's estimate using early outbreak case data. We also estimate the effectiveness of interventions using observations before and after their introduction. As the final epidemic size is linked to the timing of interventions in an exponential fashion, a simple empirical formula is provided to guide policy-making. It suggests that early implementation could significantly decrease final size. We also compare our model to one with typical symptoms by excluding moderate ones. The model with only typical symptoms overestimates the basic reproduction number and effectiveness of control measures, and exaggerates changes in peak size attributable to the timing of interventions. In addition, uncertainty about how moderate symptoms affect the basic reproduction number is considered, and PRCC (Partial rank correlation coefficient) is used to analyze the global sensitivity of relevant parameters. Possible control strategies are evaluated through numerical simulations and sensitivity analysis, indicating that simultaneously strengthening contact-tracing and effectiveness of isolation in hospital would be most effective. In this study, we show that asymptomatic Ebola infections may have implications for policy-making.
Collapse
Affiliation(s)
- Joan Ponce
- Department of Mathematics, Purdue University, West Lafayette, IN 47907, USA.
| | - Yiqiang Zheng
- Department of Mathematics, Purdue University, West Lafayette, IN 47907, USA.
| | - Guang Lin
- Department of Mathematics, Purdue University, West Lafayette, IN 47907, USA; School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA.
| | - Zhilan Feng
- Department of Mathematics, Purdue University, West Lafayette, IN 47907, USA.
| |
Collapse
|
40
|
Tuncer N, Mohanakumar C, Swanson S, Martcheva M. Efficacy of control measures in the control of Ebola, Liberia 2014-2015. JOURNAL OF BIOLOGICAL DYNAMICS 2018; 12:913-937. [PMID: 30355048 DOI: 10.1080/17513758.2018.1535095] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/23/2017] [Accepted: 10/06/2018] [Indexed: 06/08/2023]
Abstract
The largest outbreak of Ebola to date is the 2014 West Africa Ebola outbreak, with more than 10,000 cases and over 4000 deaths reported in Liberia alone. To control the spread of the outbreak, multiple interventions were implemented: identification and isolation of cases, contact tracing, quarantining of suspected contacts, proper personal protection, safely conducted burials, improved education, social awareness and individual protective measures. Devising rigorous methodologies for the evaluation of the effectiveness of the control measures implemented to stop an outbreak is of paramount importance. In this paper, we evaluate the effectiveness of the 2014 Ebola outbreak interventions. We rely on model selection to determine the best model that explains the 2014 Ebola outbreak data in Liberia which is the simplest model with a social distancing term. We couple structural and practical identifiability analysis with the computation of confidence intervals to pinpoint the uncertainty in the parameter estimations. Finally, we evaluate the efficacy of control measures using the Ebola model with social distancing. Among all the control measures, we find that social distancing had the most impact on the control of the 2014 Ebola epidemic in Libreria followed by isolation and quarantining.
Collapse
Affiliation(s)
- Necibe Tuncer
- a Department of Mathematical Sciences , Florida Atlantic University , Boca Raton , FL , USA
| | - Chindu Mohanakumar
- b Department of Mathematics , University of Florida , Gainesville , FL , USA
| | - Samuel Swanson
- b Department of Mathematics , University of Florida , Gainesville , FL , USA
| | - Maia Martcheva
- b Department of Mathematics , University of Florida , Gainesville , FL , USA
| |
Collapse
|
41
|
Kabli K, El Moujaddid S, Niri K, Tridane A. Cooperative system analysis of the Ebola virus epidemic model. Infect Dis Model 2018; 3:145-159. [PMID: 30839882 PMCID: PMC6326236 DOI: 10.1016/j.idm.2018.09.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Revised: 09/03/2018] [Accepted: 09/16/2018] [Indexed: 11/27/2022] Open
Abstract
This paper aims to study the global stability of an Ebola virus epidemic model. Although this epidemic ended in September 2015, it devastated several West African countries and mobilized the international community. With the recent cases of Ebola in the Democratic Republic of the Congo (DRC), the threat of the reappearance of this fatal disease remains. Therefore, we are obligated to be prepared for a possible re-emerging of the disease. In this work, we investigate the global stability analysis via the theory of cooperative systems, and we determine the conditions that lead to global stability diseases free and endemic equilibrium.
Collapse
Affiliation(s)
- Karima Kabli
- Department of Mathematics and Computing, Ain Chock Science Faculty, Hassan II University, Casablanca, Morocco
| | - Soumia El Moujaddid
- Department of Mathematics and Computing, Ain Chock Science Faculty, Hassan II University, Casablanca, Morocco
| | - Khadija Niri
- Department of Mathematics and Computing, Ain Chock Science Faculty, Hassan II University, Casablanca, Morocco
| | - Abdessamad Tridane
- Department of Mathematical Sciences, United Arab Emirates University, P.O. Box 15551, Al Ain, United Arab Emirates
| |
Collapse
|
42
|
Bodine EN, Cook C, Shorten M. The potential impact of a prophylactic vaccine for Ebola in Sierra Leone. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2018; 15:337-359. [PMID: 29161839 DOI: 10.3934/mbe.2018015] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
The 2014 outbreak of Ebola virus disease (EVD) in West Africa was multinational and of an unprecedented scale primarily affecting the countries of Guinea, Liberia, and Sierra Leone. One of the qualities that makes EVD of high public concern is its potential for extremely high mortality rates (up to 90%). A prophylactic vaccine for ebolavirus (rVSV-ZEBOV) has been developed, and clinical trials show near-perfect efficacy. We have developed an ordinary differential equations model that simulates an EVD epidemic and takes into account (1) transmission through contact with infectious EVD individuals and deceased EVD bodies, (2) the heterogeneity of the risk of becoming infected with EVD, and (3) the increased survival rate of infected EVD patients due to greater access to trained healthcare providers. Using fitted parameter values that closely simulate the dynamics of the 2014 outbreak in Sierra Leone, we utilize our model to predict the potential impact of a prophylactic vaccine for the ebolavirus using various vaccination strategies including ring vaccination. Our results show that an rVSV-ZEBOV vaccination coverage as low as 40% in the general population and 95% in healthcare workers will prevent another catastrophic outbreak like the 2014 outbreak from occurring.
Collapse
Affiliation(s)
- Erin N Bodine
- Rhodes College, Department of Mathematics and Computer Science, 2000 N. Parkway, Memphis, TN 38112, United States
| | - Connor Cook
- Rhodes College, Department of Mathematics and Computer Science, 2000 N. Parkway, Memphis, TN 38112, United States
| | - Mikayla Shorten
- Rhodes College, Department of Mathematics and Computer Science, 2000 N. Parkway, Memphis, TN 38112, United States
| |
Collapse
|
43
|
Wiratsudakul A, Suparit P, Modchang C. Dynamics of Zika virus outbreaks: an overview of mathematical modeling approaches. PeerJ 2018; 6:e4526. [PMID: 29593941 PMCID: PMC5866925 DOI: 10.7717/peerj.4526] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2017] [Accepted: 03/02/2018] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND The Zika virus was first discovered in 1947. It was neglected until a major outbreak occurred on Yap Island, Micronesia, in 2007. Teratogenic effects resulting in microcephaly in newborn infants is the greatest public health threat. In 2016, the Zika virus epidemic was declared as a Public Health Emergency of International Concern (PHEIC). Consequently, mathematical models were constructed to explicitly elucidate related transmission dynamics. SURVEY METHODOLOGY In this review article, two steps of journal article searching were performed. First, we attempted to identify mathematical models previously applied to the study of vector-borne diseases using the search terms "dynamics," "mathematical model," "modeling," and "vector-borne" together with the names of vector-borne diseases including chikungunya, dengue, malaria, West Nile, and Zika. Then the identified types of model were further investigated. Second, we narrowed down our survey to focus on only Zika virus research. The terms we searched for were "compartmental," "spatial," "metapopulation," "network," "individual-based," "agent-based" AND "Zika." All relevant studies were included regardless of the year of publication. We have collected research articles that were published before August 2017 based on our search criteria. In this publication survey, we explored the Google Scholar and PubMed databases. RESULTS We found five basic model architectures previously applied to vector-borne virus studies, particularly in Zika virus simulations. These include compartmental, spatial, metapopulation, network, and individual-based models. We found that Zika models carried out for early epidemics were mostly fit into compartmental structures and were less complicated compared to the more recent ones. Simple models are still commonly used for the timely assessment of epidemics. Nevertheless, due to the availability of large-scale real-world data and computational power, recently there has been growing interest in more complex modeling frameworks. DISCUSSION Mathematical models are employed to explore and predict how an infectious disease spreads in the real world, evaluate the disease importation risk, and assess the effectiveness of intervention strategies. As the trends in modeling of infectious diseases have been shifting towards data-driven approaches, simple and complex models should be exploited differently. Simple models can be produced in a timely fashion to provide an estimation of the possible impacts. In contrast, complex models integrating real-world data require more time to develop but are far more realistic. The preparation of complicated modeling frameworks prior to the outbreaks is recommended, including the case of future Zika epidemic preparation.
Collapse
Affiliation(s)
- Anuwat Wiratsudakul
- Department of Clinical Sciences and Public Health, Faculty of Veterinary Science, Mahidol University, Phutthamonthon, Nakhon Pathom, Thailand
- The Monitoring and Surveillance Center for Zoonotic Diseases in Wildlife and Exotic Animals, Faculty of Veterinary Science, Mahidol University, Phutthamonthon, Nakhon Pathom, Thailand
| | - Parinya Suparit
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Ratchathewi, Bangkok, Thailand
| | - Charin Modchang
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Ratchathewi, Bangkok, Thailand
- Centre of Excellence in Mathematics, CHE, Ratchathewi, Bangkok, Thailand
| |
Collapse
|
44
|
Sareen S, Sood SK, Gupta SK. IoT-based cloud framework to control Ebola virus outbreak. JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING 2018; 9:459-476. [PMID: 32218876 PMCID: PMC7091278 DOI: 10.1007/s12652-016-0427-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2016] [Accepted: 10/11/2016] [Indexed: 05/10/2023]
Abstract
Ebola is a deadly infectious virus that spreads very quickly through human-to-human transmission and sometimes death. The continuous detection and remote monitoring of infected patients are required in order to prevent the spread of Ebola virus disease (EVD). Healthcare services based on Internet of Things (IoT) and cloud computing technologies are emerging as a more effective and proactive solution which provides remote continuous monitoring of patients. A novel architecture based on Radio Frequency Identification Device (RFID), wearable sensor technology, and cloud computing infrastructure is proposed for the detection and monitoring of Ebola infected patients. The aim of this work is to prevent the spreading of the infection at the early stage of the outbreak. The J48 decision tree is used to evaluate the level of infection in a user depending on his symptoms. RFID is used to automatically sense the close proximity interactions (CPIs) between users. Temporal Network Analysis (TNA) is applied to describe and monitor the current state of the outbreak using the CPI data. The performance and accuracy of our proposed model are evaluated on Amazon EC2 cloud using synthetic data of two million users. Our proposed model provided 94 % accuracy for the classification and 92 % of the resource utilization.
Collapse
Affiliation(s)
- Sanjay Sareen
- Computer Section, Guru Nanak Dev University, Amritsar, Punjab India
- I. K. Gujral Punjab Technical University, Kapurthala, Punjab India
| | - Sandeep K. Sood
- Computer Science and Engineering Department, Guru Nanak Dev University, Regional Campus, Gurdaspur, Punjab India
| | - Sunil Kumar Gupta
- Computer Science and Engineering Department, Beant College of Engineering and Technology, Gurdaspur, Punjab India
| |
Collapse
|
45
|
Contact tracing with a real-time location system: A case study of increasing relative effectiveness in an emergency department. Am J Infect Control 2017; 45:1308-1311. [PMID: 28967513 PMCID: PMC7115342 DOI: 10.1016/j.ajic.2017.08.014] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2017] [Revised: 08/13/2017] [Accepted: 08/14/2017] [Indexed: 11/27/2022]
Abstract
Contact tracing is an essential step in infectious disease control and prevention. Using Electronic medical record (EMR) is challenging and misses a number of potential exposures. Real time location system (RTLS) doubled the potential exposures list for pertussis disease beyond the conventional method of EMR-based contact identification RTLS is more efficient and timely in the process of contact tracing. Further studies with larger sample size are needed to confirm the findings.
Background Contact tracing is the systematic method of identifying individuals potentially exposed to infectious diseases. Electronic medical record (EMR) use for contact tracing is time-consuming and may miss exposed individuals. Real-time location systems (RTLSs) may improve contact identification. Therefore, the relative effectiveness of these 2 contact tracing methodologies were evaluated. Methods During a pertussis outbreak in the United States, a retrospective case study was conducted between June 14 and August 31, 2016, to identify the contacts of confirmed pertussis cases, using EMR and RTLS data in the emergency department of a tertiary care medical center. Descriptive statistics and a paired t test (α = 0.05) were performed to compare contacts identified by EMR versus RTLS, as was correlation between pertussis patient length of stay and the number of potential contacts. Results Nine cases of pertussis presented to the emergency department during the identified time period. RTLS doubled the potential exposure list (P < .01). Length of stay had significant positive correlation with contacts identified by RTLS (ρ = 0.79; P = .01) but not with EMR (ρ = 0.43; P = .25). Conclusions RTLS doubled the potential pertussis exposures beyond EMR-based contact identification. Thus, RTLS may be a valuable addition to the practice of contact tracing and infectious disease monitoring.
Collapse
|
46
|
Evaluations of Interventions Using Mathematical Models with Exponential and Non-exponential Distributions for Disease Stages: The Case of Ebola. Bull Math Biol 2017; 79:2149-2173. [DOI: 10.1007/s11538-017-0324-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2017] [Accepted: 07/07/2017] [Indexed: 10/19/2022]
|
47
|
Saurabh S, Prateek S. Role of contact tracing in containing the 2014 Ebola outbreak: a review. Afr Health Sci 2017; 17:225-236. [PMID: 29026397 DOI: 10.4314/ahs.v17i1.28] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND The 2014 outbreak of Ebola virus disease which emerged in the month of March in the year 2014 in Guinea has been declared as a public health emergency of international concern. OBJECTIVES The objectives of the review article are to assess the role of contact tracing in the Ebola outbreak and to identify the challenges faced by the health workers while performing contact tracing. METHODS An extensive search of all materials related to the Ebola outbreak and contact tracing was carried out in PubMed, Medline, World Health Organization website and Google Scholar search engines. Keywords used in the search included Ebola virus disease, West-Africa, contact tracing, World Health Organization. Overall 60 articles were selected and included in the discussion. RESULTS Contact tracing is an important strategy in epidemiology and refers to the identification and diagnosis of those individuals who have come in contact with an infected person. It ultimately aims to reduce the time span required to detect and treat a case of an infectious disease and hence significantly minimize the risk of transmission to the subsequent susceptible individuals. In-fact, contact tracing continues to remain an important measure, as it aids the epidemiologist in containing the infection. CONCLUSION The strategy of contact tracing has a great potential to significantly reduce the incidence of cases of Ebola virus disease. However, its success is eventually determined by the level of trust between the community and the public health system and the quality of the diagnostic & treatment services.
Collapse
|
48
|
A systematic review of early modelling studies of Ebola virus disease in West Africa. Epidemiol Infect 2017; 145:1069-1094. [PMID: 28166851 DOI: 10.1017/s0950268817000164] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Phenomenological and mechanistic models are widely used to assist resource planning for pandemics and emerging infections. We conducted a systematic review, to compare methods and outputs of published phenomenological and mechanistic modelling studies pertaining to the 2013-2016 Ebola virus disease (EVD) epidemics in four West African countries - Sierra Leone, Liberia, Guinea and Nigeria. We searched Pubmed, Embase and Scopus databases for relevant English language publications up to December 2015. Of the 874 articles identified, 41 met our inclusion criteria. We evaluated these selected studies based on: the sources of the case data used, and modelling approaches, compartments used, population mixing assumptions, model fitting and calibration approaches, sensitivity analysis used and data bias considerations. We synthesised results of the estimated epidemiological parameters: basic reproductive number (R 0), serial interval, latent period, infectious period and case fatality rate, and examined their relationships. The median of the estimated mean R 0 values were between 1·30 and 1·84 in Sierra Leone, Liberia and Guinea. Much higher R 0 value of 9·01 was described for Nigeria. We investigated several issues with uncertainty around EVD modes of transmission, and unknown observation biases from early reported case data. We found that epidemic models offered R 0 mean estimates which are country-specific, but these estimates are not associating with the use of several key disease parameters within the plausible ranges. We find simple models generally yielded similar estimates of R 0 compared with more complex models. Models that accounted for data uncertainty issues have offered a higher case forecast compared with actual case observation. Simple model which offers transparency to public health policy makers could play a critical role for advising rapid policy decisions under an epidemic emergency.
Collapse
|
49
|
Ajelli M, Merler S, Fumanelli L, Pastore Y Piontti A, Dean NE, Longini IM, Halloran ME, Vespignani A. Spatiotemporal dynamics of the Ebola epidemic in Guinea and implications for vaccination and disease elimination: a computational modeling analysis. BMC Med 2016; 14:130. [PMID: 27600737 PMCID: PMC5013652 DOI: 10.1186/s12916-016-0678-3] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2016] [Accepted: 08/20/2016] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Among the three countries most affected by the Ebola virus disease outbreak in 2014-2015, Guinea presents an unusual spatiotemporal epidemic pattern, with several waves and a long tail in the decay of the epidemic incidence. METHODS Here, we develop a stochastic agent-based model at the level of a single household that integrates detailed data on Guinean demography, hospitals, Ebola treatment units, contact tracing, and safe burial interventions. The microsimulation-based model is used to assess the effect of each control strategy and the probability of elimination of the epidemic according to different intervention scenarios, including ring vaccination with the recombinant vesicular stomatitis virus-vectored vaccine. RESULTS The numerical results indicate that the dynamics of the Ebola epidemic in Guinea can be quantitatively explained by the timeline of the implemented interventions. In particular, the early availability of Ebola treatment units and the associated isolation of cases and safe burials helped to limit the number of Ebola cases experienced by Guinea. We provide quantitative evidence of a strong negative correlation between the time series of cases and the number of traced contacts. This result is confirmed by the computational model that suggests that contact tracing effort is a key determinant in the control and elimination of the disease. In data-driven microsimulations, we find that tracing at least 5-10 contacts per case is crucial in preventing epidemic resurgence during the epidemic elimination phase. The computational model is used to provide an analysis of the ring vaccination trial highlighting its potential effect on disease elimination. CONCLUSIONS We identify contact tracing as one of the key determinants of the epidemic's behavior in Guinea, and we show that the early availability of Ebola treatment unit beds helped to limit the number of Ebola cases in Guinea.
Collapse
Affiliation(s)
- Marco Ajelli
- Bruno Kessler Foundation, Via Sommarive 18, Trento, 38123, Italy
| | - Stefano Merler
- Bruno Kessler Foundation, Via Sommarive 18, Trento, 38123, Italy
| | - Laura Fumanelli
- Bruno Kessler Foundation, Via Sommarive 18, Trento, 38123, Italy
| | - Ana Pastore Y Piontti
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, 360 Huntington Ave, Boston, MA, 02115, USA
| | - Natalie E Dean
- Department of Biostatistics, University of Florida, 2004 Mowry Rd, Gainesville, FL, 32611, USA
| | - Ira M Longini
- Department of Biostatistics, University of Florida, 2004 Mowry Rd, Gainesville, FL, 32611, USA
| | - M Elizabeth Halloran
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N, Seattle, WA, 98109, USA.,School of Public Health, University of Washington, 1959 NE Pacific Street, Seattle, WA, 98195, USA
| | - Alessandro Vespignani
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, 360 Huntington Ave, Boston, MA, 02115, USA. .,Institute for Quantitative Social Sciences at Harvard University, 1737 Cambridge St, Cambridge, MA, 02138, USA. .,Institute for Scientific Interchange Foundation, Via Alassio 11/c, Turin, 10126, Italy.
| |
Collapse
|
50
|
Wong V, Cooney D, Bar-Yam Y. Beyond Contact Tracing: Community-Based Early Detection for Ebola Response. PLOS CURRENTS 2016; 8:ecurrents.outbreaks.322427f4c3cc2b9c1a5b3395e7d20894. [PMID: 27486552 PMCID: PMC4946441 DOI: 10.1371/currents.outbreaks.322427f4c3cc2b9c1a5b3395e7d20894] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
INTRODUCTION The 2014 Ebola outbreak in West Africa raised many questions about the control of infectious disease in an increasingly connected global society. Limited availability of contact information made contact tracing diffcult or impractical in combating the outbreak. METHODS We consider the development of multi-scale public health strategies that act on individual and community levels. We simulate policies for community-level response aimed at early screening all members of a community, as well as travel restrictions to prevent inter-community transmission. RESULTS Our analysis shows the policies to be effective even at a relatively low level of compliance and for a variety of local and long range contact transmission networks. In our simulations, 40% of individuals conforming to these policies is enough to stop the outbreak. Simulations with a 50% compliance rate are consistent with the case counts in Liberia during the period of rapid decline after mid September, 2014. We also find the travel restriction to be effective at reducing the risks associated with compliance substantially below the 40% level, shortening the outbreak and enabling efforts to be focused on affected areas. DISCUSSION Our results suggest that the multi-scale approach can be used to further evolve public health strategy for defeating emerging epidemics.
Collapse
Affiliation(s)
- Vincent Wong
- New England Complex Systems Institute, Cambridge, MA, USA
| | - Daniel Cooney
- New England Complex Systems Institute, Cambridge, MA, USA
| | - Yaneer Bar-Yam
- New England Complex Systems Institute, Cambridge, MA, USA
| |
Collapse
|