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1.
BMC Infect Dis ; 22(1): 514, 2022 Jun 02.
Article in English | MEDLINE | ID: covidwho-1874998

ABSTRACT

BACKGROUND: The city of Melbourne, Australia experienced two waves of the COVID-19 epidemic peaking, the first in March and a more substantial wave in July 2020. During the second wave, a series of control measure were progressively introduced that initially slowed the growth of the epidemic then resulted in decreasing cases until there was no detectable local transmission. METHODS: To determine the relative efficacy of the progressively introduced intervention measures, we modelled the second wave as a series of exponential growth and decay curves. We used a linear regression of the log of daily cases vs time, using a four-segment linear spline model corresponding to implementation of the three successive major public health measures. The primary model used all reported cases between 14 June and 15 September 2020 then compared the projection of the model with observed cases predicting future case trajectory up until the 31 October 2020 to assess the use of exponential models in projecting the future course and planning future interventions. The main outcome measures were the exponential daily growth constants, analysis of residuals and estimates of the 95% confidence intervals for the expected case distributions, comparison of predicted daily cases. RESULTS: The exponential growth/decay constants in the primary analysis were: 0.122 (s.e. 0.004), 0.035 (s.e. 0.005), - 0.037 (s.e. 0.011), and - 0.069 (s.e. 0.003) for the initial growth rate, Stage 3, Stage 3 + compulsory masks and Stage 4, respectively. Extrapolation of the regression model from the 14 September to the 31 October matched the decline in observed cases over this period. CONCLUSIONS: The four-segment exponential model provided an excellent fit of the observed reported case data and predicted the day-to-day range of expected cases. The extrapolated regression accurately predicted the decline leading to epidemic control in Melbourne.


Subject(s)
COVID-19 , Epidemics , Australia/epidemiology , COVID-19/epidemiology , COVID-19/prevention & control , Forecasting , Humans , Public Health
2.
Vaccine ; 40(28): 3821-3824, 2022 Jun 21.
Article in English | MEDLINE | ID: covidwho-1852215

ABSTRACT

Immunity to SARS-CoV-2 following vaccination wanes over time in a non-linear fashion, making modelling of likely population impacts of COVID-19 policy options challenging. We observed that it was possible to mathematize non-linear waning of vaccine effectiveness (VE) on the percentage scale as linear waning on the log-odds scale, and developed a random effects logistic regression equation based on UK Health Security Agency data to model VE against Omicron following two and three doses of a COVID-19 vaccine. VE on the odds scale reduced by 47% per month for symptomatic infection after two vaccine doses, lessening to 35% per month for hospitalisation. Waning on the odds scale after triple dose vaccines was 35% per month for symptomatic disease and 19% for hospitalisation. This log-odds system for estimating waning and boosting of COVID-19 VE provides a simple solution that may be used to parametrize SARS-CoV-2 immunity over time parsimoniously in epidemiological models.


Subject(s)
COVID-19 Vaccines , COVID-19 , COVID-19/epidemiology , COVID-19/prevention & control , Humans , SARS-CoV-2 , Vaccination
3.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-330755

ABSTRACT

Immunity to SARS-CoV-2 following vaccination wanes over time in a non-linear fashion, making modelling of likely population impacts of COVID-19 policy options challenging. We observed that it was possible to mathematize non-linear waning of vaccine effectiveness (VE) on the percentage scale as linear waning on the log-odds scale, and developed a random effects logistic regression equation based on UK Health Security Agency data to model VE against Omicron following two and three doses of a COVID-19 vaccine. VE on the odds scale reduced by 47% per month for symptomatic infection after two vaccine doses, lessening to 35% per month for hospitalisation. Waning on the odds scale after triple dose vaccines was 35% per month for symptomatic disease and 19% for hospitalisation. This log-odds system for estimating waning and boosting of COVID-19 VE provides a simple solution that may be used to parametrize SARS-CoV-2 immunity over time parsimoniously in epidemiological models.

4.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-329911

ABSTRACT

Between June and August 2020, an agent-based model was used to project rates of COVID-19 infection incidence and cases diagnosed as positive from 15 September to 31 October 2020 for 72 geographic settings. Five scenarios were modelled: a baseline scenario where no future changes were made to existing restrictions, and four scenarios representing small or moderate changes in restrictions at two intervals. Post hoc, upper and lower bounds for number of diagnosed Covid-19 cases were compared with actual data collected during the prediction window. A regression analysis with 17 covariates was performed to determine correlates of accurate projections. It was found that the actual data fell within the lower and upper bounds in 27 settings and out of bounds in 45 settings. The only statistically significant predictor of actual data within the predicted bounds was correct assumptions about future policy changes (OR = 15.04;95%CI 2.20-208.70;p = 0.016). Frequent changes in restrictions implemented by governments, which the modelling team was not always able to predict, in part explains why the majority of model projections were inaccurate compared with actual outcomes and supports revision of projections when policies are changed as well as the importance of modelling teams collaborating with policy experts.

5.
Emerg Infect Dis ; 28(5): 1053-1055, 2022 05.
Article in English | MEDLINE | ID: covidwho-1736726

ABSTRACT

The Pacific Island country of Vanuatu is considering strategies to remove border restrictions implemented during 2020 to prevent imported coronavirus disease. We performed mathematical modeling to estimate the number of infectious travelers who had different entry scenarios and testing strategies. Travel bubbles and testing on entry have the greatest importation risk reduction.


Subject(s)
COVID-19 , Quarantine , COVID-19/prevention & control , Humans , SARS-CoV-2 , Travel , Vanuatu
6.
BMC Infect Dis ; 22(1): 232, 2022 Mar 07.
Article in English | MEDLINE | ID: covidwho-1731519

ABSTRACT

BACKGROUND: In settings with zero community transmission, any new SARS-CoV-2 outbreaks are likely to be the result of random incursions. The level of restrictions in place at the time of the incursion is likely to considerably affect possible outbreak trajectories, but the probability that a large outbreak eventuates is not known. METHODS: We used an agent-based model to investigate the relationship between ongoing restrictions and behavioural factors, and the probability of an incursion causing an outbreak and the resulting growth rate. We applied our model to the state of Victoria, Australia, which has reached zero community transmission as of November 2020. RESULTS: We found that a future incursion has a 45% probability of causing an outbreak (defined as a 7-day average of > 5 new cases per day within 60 days) if no restrictions were in place, decreasing to 23% with a mandatory masks policy, density restrictions on venues such as restaurants, and if employees worked from home where possible. A drop in community symptomatic testing rates was associated with up to a 10-percentage point increase in outbreak probability, highlighting the importance of maintaining high testing rates as part of a suppression strategy. CONCLUSIONS: Because the chance of an incursion occurring is closely related to border controls, outbreak risk management strategies require an integrated approaching spanning border controls, ongoing restrictions, and plans for response. Each individual restriction or control strategy reduces the risk of an outbreak. They can be traded off against each other, but if too many are removed there is a danger of accumulating an unsafe level of risk. The outbreak probabilities estimated in this study are of particular relevance in assessing the downstream risks associated with increased international travel.


Subject(s)
COVID-19 , COVID-19/epidemiology , COVID-19/prevention & control , Disease Outbreaks/prevention & control , Humans , Longitudinal Studies , SARS-CoV-2 , Victoria/epidemiology
7.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-325517

ABSTRACT

Background: To prevent the catastrophic health and economic consequences from COVID-19 epidemics, nations had to respond with swift public health interventions to achieve no community transmission outside of quarantine. However, the exact characteristics of an outbreak that trigger these measures are poorly defined. We aimed to assess the critical timing and extent of interventions in Australia. Methods: We developed a practical model using existing epidemics data in Australia. We quantified the effective combinations of public health interventions and the critical number of daily cases for intervention commencement. We assessed the impact of increasing transmissibility from new variants and the effect of vaccination coverage on the critical timing and extent of interventions. Findings: We found that in the past COVID-19 outbreaks in four Australian states, the number of reported cases on the day that interventions commenced strongly predicted the size and duration of the outbreaks. In the early phase of an outbreak, containing a wild-type dominant epidemic to a low level (≤10 cases/day) required effective combinations of social distancing and face mask use interventions to be commenced before the number of daily reported cases reaches 6 cases. Containing epidemics from alpha variant would require more stringent interventions that commenced earlier. For delta variant, public health interventions alone will not contain the epidemic, unless with a moderate vaccination coverage (≥50%). Interpretation: Our study highlights the importance of early and decisive action in the initial phase of an outbreak if governments aimed for zero community transmission. Vaccination is essential for containing variants.Funding Information: LZ is supported by the National Natural Science Foundation of China (grant number: 8191101420), Thousand Talents Plan Professorship for Young Scholars (Grant number: 3111500001);Xi’an Jiaotong University Basic Research and Profession Grant (Grant number: xtr022019003) and Xi’an Jiaotong University Young Talent Support Program (Grant number: YX6J004). The study is supported by Bill and Melinda Gates Foundation. Declaration of Interests: The authors declare no competing interests.

8.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-318426

ABSTRACT

The COVID-19-related economic crisis and food- and health-system disruptions threaten to exacerbate undernutrition in low- and middle-income countries (LMIC). We used three modelling tools (MIRAGRODEP, Lives Saved Tool, and Optima Nutrition Tool) to estimate impacts on child stunting, wasting, and mortality, maternal anemia, children born to low BMI women, and future productivity losses for three scenarios across 2020–2022 (n = 118 LMICs). We also estimated the additional cost of mitigation for six nutrition interventions to maximize non-stunted and alive children. By 2022 COVID-19 could result in an additional 9.3 million wasted and 2.6 million stunted children, 168,000 additional child-deaths 2.1 million maternal anemia cases, 2.1 million children born to low BMI women and US$29.7 billion future productivity losses due to excess stunting and child mortality. An additional $1.2 billion per year is needed to mitigate these effects. Governments and donors must maintain nutrition as a priority, continue to support resilient systems, and ensure efficient use of new and existing resources.

9.
Int J Infect Dis ; 115: 154-165, 2022 Feb.
Article in English | MEDLINE | ID: covidwho-1664990

ABSTRACT

OBJECTIVES: The exact characteristics of a coronavirus disease 2019 (COVID-19) outbreak that trigger public health interventions are poorly defined. The aim of this study was to assess the critical timing and extent of public health interventions to contain COVID-19 outbreaks in Australia. METHODS: A practical model was developed using existing epidemic data in Australia. The effective combinations of public health interventions and the critical number of daily cases for intervention commencement under various scenarios of changes in transmissibility of new variants and vaccination coverage were quantified. RESULTS: In the past COVID-19 outbreaks in four Australian states, the number of reported cases on the day that interventions commenced strongly predicted the size and duration of the outbreaks. In the early phase of an outbreak, containing a wildtype-dominant epidemic to a low level (≤10 cases/day) would require effective combinations of social distancing and face mask use interventions to be commenced before the number of daily reported cases reaches six. Containing an Alpha-dominant epidemic would require more stringent interventions that commence earlier. For the Delta variant, public health interventions alone would not contain the epidemic unless the vaccination coverage was ≥70%. CONCLUSIONS: This study highlights the importance of early and decisive action in the initial phase of an outbreak. Vaccination is essential for containing variants.


Subject(s)
COVID-19 , SARS-CoV-2 , Australia/epidemiology , Disease Outbreaks , Humans , Public Health
10.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-295129

ABSTRACT

Background: Reducing unmet need for modern contraception and expanding access to quality maternal health (MH) services are priorities for improving women’s health and economic empowerment including in Small Island Developing States in the Pacific and Caribbean. We estimated health benefits and return-on-investment for contraceptive and MH interventions to help ensure appropriate prioritization.<br><br>Methods: Contraceptive and MH interventions were scaled linearly from 2022 (following COVID-19 disruptions) to reach zero unmet need for modern contraception and 95% MH intervention coverage by 2030. Five Pacific (Kiribati, Samoa, Solomon Islands, Tonga, and Vanuatu) and four Caribbean (Barbados, Guyana, Jamaica, and Saint Lucia) countries were considered based on population survey availability. Health outcomes were estimated and converted to economic benefits, and compared for business-as-usual (BAU) (coverage maintained) and coverage-targets-achieved scenarios.<br><br>Findings: An additional US$13.4M (US$10.9M-US$16.0M) is needed over 2020-2030 for the five Pacific countries to reach coverage targets (19% more than US$70.5M to maintain BAU). This could avert 126,000 (40%) unintended pregnancies, 2,200 (28%) stillbirths, and 121 (29%) maternal deaths and bring an elevenfold economic benefit of US$149.7M (US$54.5M-US$214.7M) by 2040. For the four Caribbean countries, an additional US$18.8M (US$15.3M-US$22.4M) is needed to reach targets (5% more than US$342.3M to maintain BAU). This could avert 127,000 (23%) unintended pregnancies, 3,600 (23%) stillbirths, and 221 (25%) maternal deaths and bring a twentyfold economic benefit of US$375.4M (US$137.9M-US$540.6M) by 2040.<br><br>Interpretation: Achieving full coverage of contraceptive and maternal health services in the Pacific and Caribbean is likely to be affordable and have high return-on-investment.<br><br>Funding Information: Funding for this study was provided by UNFPA.<br><br>Declaration of Interests: None declared.<br>

11.
PLoS Comput Biol ; 17(7): e1009149, 2021 07.
Article in English | MEDLINE | ID: covidwho-1325366

ABSTRACT

The COVID-19 pandemic has created an urgent need for models that can project epidemic trends, explore intervention scenarios, and estimate resource needs. Here we describe the methodology of Covasim (COVID-19 Agent-based Simulator), an open-source model developed to help address these questions. Covasim includes country-specific demographic information on age structure and population size; realistic transmission networks in different social layers, including households, schools, workplaces, long-term care facilities, and communities; age-specific disease outcomes; and intrahost viral dynamics, including viral-load-based transmissibility. Covasim also supports an extensive set of interventions, including non-pharmaceutical interventions, such as physical distancing and protective equipment; pharmaceutical interventions, including vaccination; and testing interventions, such as symptomatic and asymptomatic testing, isolation, contact tracing, and quarantine. These interventions can incorporate the effects of delays, loss-to-follow-up, micro-targeting, and other factors. Implemented in pure Python, Covasim has been designed with equal emphasis on performance, ease of use, and flexibility: realistic and highly customized scenarios can be run on a standard laptop in under a minute. In collaboration with local health agencies and policymakers, Covasim has already been applied to examine epidemic dynamics and inform policy decisions in more than a dozen countries in Africa, Asia-Pacific, Europe, and North America.


Subject(s)
COVID-19 , Models, Biological , SARS-CoV-2 , Systems Analysis , Basic Reproduction Number , COVID-19/etiology , COVID-19/prevention & control , COVID-19/transmission , COVID-19 Testing , COVID-19 Vaccines , Computational Biology , Computer Simulation , Contact Tracing , Disease Progression , Hand Disinfection , Host Microbial Interactions , Humans , Masks , Mathematical Concepts , Pandemics , Physical Distancing , Quarantine , Software
12.
PLoS One ; 16(7): e0253510, 2021.
Article in English | MEDLINE | ID: covidwho-1319515

ABSTRACT

BACKGROUND: Whilst evidence of use of face masks in reducing COVID-19 cases is increasing, the impact of mandatory use across a large population has been difficult to assess. Introduction of mandatory mask use on July 22, 2020 during a resurgence of COVID-19 in Melbourne, Australia created a situation that facilitated an assessment of the impact of the policy on the epidemic growth rate as its introduction occurred in the absence of other changes to restrictions. METHODS AND FINDINGS: Exponential epidemic growth or decay rates in daily COVID-19 diagnoses were estimated using a non-weighted linear regression of the natural logarithm of the daily cases against time, using a linear spline model with one knot (lspline package in R v 3.6.3). The model's two linear segments pivot around the hinge day, on which the mask policy began to take effect, 8 days following the introduction of the policy. We used two forms of data to assess change in mask usage: images of people wearing masks in public places obtained from a major media outlet and population-based survey data. Potential confounding factors (including daily COVID-19 tests, number of COVID-19 cases among population subsets affected differentially by the mask policy-e.g., healthcare workers) were examined for their impact on the results. Daily cases fitted an exponential growth in the first log-linear segment (k = +0.042, s.e. = 0.007), and fitted an exponential decay in the second (k = -0.023, s.e. = 0.017) log-linear segment. Over a range of reported serial intervals for SARS-CoV-2 infection, these growth rates correspond to a 22-33% reduction in an effective reproduction ratio before and after mandatory mask use. Analysis of images of people in public spaces showed mask usage rose from approximately 43% to 97%. Analysis of survey data found that on the third day before policy introduction, 44% of participants reported "often" or "always" wearing a mask; on the fourth day after, 100% reported "always" doing so. No potentially confounding factors were associated with the observed change in growth rates. CONCLUSIONS: The mandatory mask use policy substantially increased public use of masks and was associated with a significant decline in new COVID-19 cases after introduction of the policy. This study strongly supports the use of masks for controlling epidemics in the broader community.


Subject(s)
COVID-19/epidemiology , COVID-19/prevention & control , Masks/statistics & numerical data , Policy , Australia/epidemiology , Cities/epidemiology , Health Behavior , Humans , Multivariate Analysis , Pandemics/prevention & control
13.
BMJ Open ; 11(4): e045941, 2021 04 20.
Article in English | MEDLINE | ID: covidwho-1195844

ABSTRACT

OBJECTIVES: The early stages of the COVID-19 pandemic illustrated that SARS-CoV-2, the virus that causes the disease, has the potential to spread exponentially. Therefore, as long as a substantial proportion of the population remains susceptible to infection, the potential for new epidemic waves persists even in settings with low numbers of active COVID-19 infections, unless sufficient countermeasures are in place. We aim to quantify vulnerability to resurgences in COVID-19 transmission under variations in the levels of testing, tracing and mask usage. SETTING: The Australian state of New South Wales (NSW), a setting with prolonged low transmission, high mobility, non-universal mask usage and a well-functioning test-and-trace system. PARTICIPANTS: None (simulation study). RESULTS: We find that the relative impact of masks is greatest when testing and tracing rates are lower and vice versa. Scenarios with very high testing rates (90% of people with symptoms, plus 90% of people with a known history of contact with a confirmed case) were estimated to lead to a robustly controlled epidemic. However, across comparable levels of mask uptake and contact tracing, the number of infections over this period was projected to be 2-3 times higher if the testing rate was 80% instead of 90%, 8-12 times higher if the testing rate was 65% or 30-50 times higher with a 50% testing rate. In reality, NSW diagnosed 254 locally acquired cases over this period, an outcome that had a moderate probability in the model (10%-18%) assuming low mask uptake (0%-25%), even in the presence of extremely high testing (90%) and near-perfect community contact tracing (75%-100%), and a considerably higher probability if testing or tracing were at lower levels. CONCLUSIONS: Our work suggests that testing, tracing and masks can all be effective means of controlling transmission. A multifaceted strategy that combines all three, alongside continued hygiene and distancing protocols, is likely to be the most robust means of controlling transmission of SARS-CoV-2.


Subject(s)
COVID-19 , Pandemics , Australia/epidemiology , Contact Tracing , Humans , Masks , New South Wales/epidemiology , SARS-CoV-2
15.
Med J Aust ; 214(2): 79-83, 2021 02.
Article in English | MEDLINE | ID: covidwho-934605

ABSTRACT

OBJECTIVES: To assess the risks associated with relaxing coronavirus disease 2019 (COVID-19)-related physical distancing restrictions and lockdown policies during a period of low viral transmission. DESIGN: Network-based viral transmission risks in households, schools, workplaces, and a variety of community spaces and activities were simulated in an agent-based model, Covasim. SETTING: The model was calibrated for a baseline scenario reflecting the epidemiological and policy environment in Victoria during March-May 2020, a period of low community viral transmission. INTERVENTION: Policy changes for easing COVID-19-related restrictions from May 2020 were simulated in the context of interventions that included testing, contact tracing (including with a smartphone app), and quarantine. MAIN OUTCOME MEASURE: Increase in detected COVID-19 cases following relaxation of restrictions. RESULTS: Policy changes that facilitate contact of individuals with large numbers of unknown people (eg, opening bars, increased public transport use) were associated with the greatest risk of COVID-19 case numbers increasing; changes leading to smaller, structured gatherings with known contacts (eg, small social gatherings, opening schools) were associated with lower risks. In our model, the rise in case numbers following some policy changes was notable only two months after their implementation. CONCLUSIONS: Removing several COVID-19-related restrictions within a short period of time should be undertaken with care, as the consequences may not be apparent for more than two months. Our findings support continuation of work from home policies (to reduce public transport use) and strategies that mitigate the risk associated with re-opening of social venues.


Subject(s)
COVID-19/prevention & control , COVID-19/transmission , Epidemiological Monitoring , Health Policy , Models, Theoretical , Physical Distancing , Quarantine , Contact Tracing/methods , Humans , Mobile Applications , Risk Assessment , SARS-CoV-2 , Smartphone , Victoria/epidemiology
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