Understanding the impact of mobility on COVID-19 spread: A hybrid gravity-metapopulation model of COVID-19.

The outbreak of the severe acute respiratory syndrome coronavirus 2 started in Wuhan, China, towards the end of 2019 and spread worldwide. The rapid spread of the disease can be attributed to many factors including its high infectiousness and the high rate of human mobility around the world. Although travel/movement restrictions and other non-pharmaceutical interventions aimed at controlling the disease spread were put in place during the early stages of the pandemic, these interventions did not stop COVID-19 spread. To better understand the impact of human mobility on the spread of COVID-19 between regions, we propose a hybrid gravity-metapopulation model of COVID-19. Our modeling framework has the flexibility of determining mobility between regions based on the distances between the regions or using data from mobile devices. In addition, our model explicitly incorporates time-dependent human mobility into the disease transmission rate, and has the potential to incorporate other factors that affect disease transmission such as facemasks, physical distancing, contact rates, etc. An important feature of this modeling framework is its ability to independently assess the contribution of each factor to disease transmission. Using a Bayesian hierarchical modeling framework, we calibrate our model to the weekly reported cases of COVID-19 in thirteen local health areas in Metro Vancouver, British Columbia (BC), Canada, from July 2020 to January 2021. We consider two main scenarios in our model calibration: using a fixed distance matrix and time-dependent weekly mobility matrices. We found that the distance matrix provides a better fit to the data, whilst the mobility matrices have the ability to explain the variance in transmission between regions. This result shows that the mobility data provides more information in terms of disease transmission than the distances between the regions.

Risk factors for COVID-19 hospitalization after COVID-19 vaccination: a population-based cohort study in Canada.

OBJECTIVES: With the uptake of COVID-19 vaccines, there is a need for population-based studies to assess risk factors for COVID-19-related hospitalization after vaccination and how they differ from unvaccinated individuals. METHODS: We used data from the British Columbia COVID-19 Cohort, a population-based cohort that includes all individuals (aged ≥18 years) who tested positive for SARS-CoV-2 by real-time reverse transcription-polymerase chain reaction from January 1, 2021 (after the start of vaccination program) to December 31, 2021. We used multivariable logistic regression models to assess COVID-19-related hospitalization risk by vaccination status and age group among confirmed COVID-19 cases. RESULTS: Of the 162,509 COVID-19 cases included in the analysis, 8,546 (5.3%) required hospitalization. Among vaccinated individuals, an increased odds of hospitalization with increasing age was observed for older age groups, namely those aged 50-59 years (odds ratio [OR] = 2.95, 95% confidence interval [CI]: 2.01-4.33), 60-69 years (OR = 4.82, 95% CI: 3.29, 7.07), 70-79 years (OR = 11.92, 95% CI: 8.02, 17.71), and ≥80 years (OR = 24.25, 95% CI: 16.02, 36.71). However, among unvaccinated individuals, there was a graded increase in odds of hospitalization with increasing age, starting at age group 30-39 years (OR = 2.14, 95% CI: 1.90, 2.41) to ≥80 years (OR = 41.95, 95% CI: 35.43, 49.67). Also, comparing all the age groups to the youngest, the observed magnitude of association was much higher among unvaccinated individuals than vaccinated ones. CONCLUSION: Alongside a number of comorbidities, our findings showed a strong association between age and COVID-19-related hospitalization, regardless of vaccination status. However, age-related hospitalization risk was reduced two-fold by vaccination, highlighting the need for vaccination in reducing the risk of severe disease and subsequent COVID-19-related hospitalization across all population groups.

Association between close interpersonal contact and vaccine hesitancy: Findings from a population-based survey in Canada

Background Vaccine hesitancy threatens efforts to bring the coronavirus disease 2019 (COVID-19) pandemic to an end. Given that social or interpersonal contact is an important driver for COVID-19 transmission, understanding the relationship between contact rates and vaccine hesitancy may help identify appropriate targets for strategic intervention. The purpose of this study was to assess the association between interpersonal contact and COVID-19 vaccine hesitancy among a sample of unvaccinated adults in the Canadian province of British Columbia (BC). Methods Unvaccinated individuals participating in the BC COVID-19 Population Mixing Patterns Survey (BC-Mix) were asked to indicate their level of agreement to the statement, “I plan to get the COVID-19 vaccine.” Multivariable multinomial logistic regression was used to assess the association between self-reported interpersonal contact and vaccine hesitancy, adjusting for age, sex, ethnicity, educational attainment, occupation, household size and region of residence. All analyses incorporated survey sampling weights based on age, sex, geography, and ethnicity. Results Results were based on survey responses collected between March 8, 2021 and December 6, 2021, by a total of 4,515 adults aged 18 years and older. Overall, 56.7% of respondents reported that they were willing to get the COVID-19 vaccine, 27.0% were unwilling and 16.3% were undecided. We found a dose-response association between interpersonal contact and vaccine hesitancy. Compared to individuals in the lowest quartile (least contact), those in the fourth quartile (highest contact), third quartile and second quartile groups were more likely to be vaccine hesitant, with adjusted odd ratios (aORs) of 2.85 (95% CI: 2.02, 4.00), 1.91(95% CI: 1.38, 2.64), 1.78 (95% CI: 1.13, 2.82), respectively. Conclusion Study findings show that among unvaccinated people in BC, vaccine hesitancy is greater among those who have high contact rates, and hence potentially at higher risk of acquiring and transmitting infection. This may also impact future uptake of booster doses.

Cohort profile: the British Columbia COVID-19 Population Mixing Patterns Survey (BC-Mix).

PURPOSE: Several non-pharmaceutical interventions, such as physical distancing, handwashing, self-isolation, and school and business closures, were implemented in British Columbia (BC) following the first laboratory-confirmed case of COVID-19 on 26 January 2020, to minimise in-person contacts that could spread infections. The BC COVID-19 Population Mixing Patterns Survey (BC-Mix) was established as a surveillance system to measure behaviour and contact patterns in BC over time to inform the timing of the easing/re-imposition of control measures. In this paper, we describe the BC-Mix survey design and the demographic characteristics of respondents. PARTICIPANTS: The ongoing repeated online survey was launched in September 2020. Participants are mainly recruited through social media platforms (including Instagram, Facebook, YouTube, WhatsApp). A follow-up survey is sent to participants 2-4 weeks after completing the baseline survey. Survey responses are weighted to BC's population by age, sex, geography and ethnicity to obtain generalisable estimates. Additional indices such as the Material and Social Deprivation Index, residential instability, economic dependency, and others are generated using census and location data. FINDINGS TO DATE: As of 26 July 2021, over 61 000 baseline survey responses were received of which 41 375 were eligible for analysis. Of the eligible participants, about 60% consented to follow-up and about 27% provided their personal health numbers for linkage with healthcare databases. Approximately 83.5% of respondents were female, 58.7% were 55 years or older, 87.5% identified as white and 45.9% had at least a university degree. After weighting, approximately 50% were female, 39% were 55 years or older, 65% identified as white and 50% had at least a university degree. FUTURE PLANS: Multiple papers describing contact patterns, physical distancing measures, regular handwashing and facemask wearing, modelling looking at impact of physical distancing measures and vaccine acceptance, hesitancy and uptake are either in progress or have been published.

The direct and indirect impact of COVID-19 pandemic on maternal and child health services in Africa: a scoping review.

INTRODUCTION: The novel coronavirus disease 2019 (COVID-19) continues to disrupt the availability and utilization of routine and emergency health care services, with differing impacts in jurisdictions across the world. In this scoping review, we set out to synthesize documentation of the direct and indirect effect of the pandemic, and national responses to it, on maternal, newborn and child health (MNCH) in Africa. METHODS: A scoping review was conducted to provide an overview of the most significant impacts identified up to March 15, 2022. We searched MEDLINE, Embase, HealthSTAR, Web of Science, PubMed, and Scopus electronic databases. We included peer reviewed literature that discussed maternal and child health in Africa during the COVID-19 pandemic, published from January 2020 to March 2022, and written in English. Papers that did not focus on the African region or an African country were excluded. A data-charting form was developed by the two reviewers to determine which themes to extract, and narrative descriptions were written about the extracted thematic areas. RESULTS: Four-hundred and seventy-eight articles were identified through our literature search and 27 were deemed appropriate for analysis. We identified three overarching themes: delayed or decreased care, disruption in service provision and utilization and mitigation strategies or recommendations. Our results show that minor consideration was given to preserving and promoting health service access and utilization for mothers and children, especially in historically underserved areas in Africa. CONCLUSIONS: Reviewed literature illuminates the need for continued prioritization of maternity services, immunization, and reproductive health services. This prioritization was not given the much-needed attention during the COVID-19 pandemic yet is necessary to shield the continent's most vulnerable population segments from the shocks of current and future global health emergencies.

COVID-19 vaccine hesitancy in Africa: a scoping review.

BACKGROUND: Vaccination against the novel coronavirus is one of the most effective strategies for combating the global Coronavirus disease (COVID-19) pandemic. However, vaccine hesitancy has emerged as a major obstacle in several regions of the world, including Africa. The objective of this rapid review was to summarize the literature on COVID-19 vaccine hesitancy in Africa. METHODS: We searched Scopus, Web of Science, African Index Medicus, and OVID Medline for studies published from January 1, 2020, to March 8, 2022, examining acceptance or hesitancy towards the COVID-19 vaccine in Africa. Study characteristics and reasons for COVID-19 vaccine acceptance were extracted from the included articles. RESULTS: A total of 71 articles met the eligibility criteria and were included in the review. Majority (n = 25, 35%) of the studies were conducted in Ethiopia. Studies conducted in Botswana, Cameroun, Cote D'Ivoire, DR Congo, Ghana, Kenya, Morocco, Mozambique, Nigeria, Somalia, South Africa, Sudan, Togo, Uganda, Zambia, Zimbabwe were also included in the review. The vaccine acceptance rate ranged from 6.9 to 97.9%. The major reasons for vaccine hesitancy were concerns with vaccine safety and side effects, lack of trust for pharmaceutical industries and misinformation or conflicting information from the media. Factors associated with positive attitudes towards the vaccine included being male, having a higher level of education, and fear of contracting the virus. CONCLUSIONS: Our review demonstrated the contextualized and multifaceted reasons inhibiting or encouraging vaccine uptake in African countries. This evidence is key to operationalizing interventions based on facts as opposed to assumptions. Our paper provided important considerations for addressing the challenge of COVID-19 vaccine hesitancy and blunting the impact of the pandemic in Africa.

Mathematical modeling of COVID-19 in British Columbia: An age-structured model with time-dependent contact rates.

Following the emergence of COVID-19 at the end of 2019, several mathematical models have been developed to study the transmission dynamics of this disease. Many of these models assume homogeneous mixing in the underlying population. However, contact rates and mixing patterns can vary dramatically among individuals depending on their age and activity level. Variation in contact rates among age groups and over time can significantly impact how well a model captures observed trends. To properly model the age-dependent dynamics of COVID-19 and understand the impacts of interventions, it is essential to consider heterogeneity arising from contact rates and mixing patterns. We developed an age-structured model that incorporates time-varying contact rates and population mixing computed from the ongoing BC Mix COVID-19 survey to study transmission dynamics of COVID-19 in British Columbia (BC), Canada. Using a Bayesian inference framework, we fit four versions of our model to weekly reported cases of COVID-19 in BC, with each version allowing different assumptions of contact rates. We show that in addition to incorporating age-specific contact rates and mixing patterns, time-dependent (weekly) contact rates are needed to adequately capture the observed transmission dynamics of COVID-19. Our approach provides a framework for explicitly including empirical contact rates in a transmission model, which removes the need to otherwise model the impact of many non-pharmaceutical interventions. Further, this approach allows projection of future cases based on clear assumptions of age-specific contact rates, as opposed to less tractable assumptions regarding transmission rates.