Prevalence and factors associated with utilisation of postnatal care in Sierra Leone: a 2019 national survey

Background Within Sub-Saharan Africa, some countries still report unacceptably high rates of maternal and perinatal morbidity and mortality, despite improvements in the utilisation of maternity care services. Postnatal care (PNC) is one of the recommended packages in the continuum of maternity care aimed at reducing maternal and neonatal mortality. This study aimed to determine the prevalence and factors associated with PNC utilisation in Sierra Leone. Methods We used Sierra Leone Demographic and Health Survey (UDHS) 2019 data of 7326 women aged 15 to 49 years. We conducted multivariable logistic regression to determine the factors associated with PNC utilisation, using SPSS version 25. Results Out of 7326 women, 6625 (90.4, 95% CI: 89.9–91.2) had at least one PNC contact for their newborn, 6646 (90.7, 95% CI: 90.2–91.5) had a postnatal check after childbirth and 6274 (85.6, 95% CI: 85.0–86.6) had PNC for both their babies and themselves. Delivery by caesarean section (aOR 8.01, 95% CI: 3.37–19.07), having a visit by a health field worker (aOR 1.80, 95% CI: 1.46–2.20), having had eight or more ANC contacts (aOR 1.37, 95% CI: 1.08–1.73), having tertiary education (aOR 2.71, 95% CI: 1.32–5.56) and having no big problems seeking permission to access healthcare (aOR 1.51, 95% CI: 1.19–1.90) were associated with higher odds of PNC utilisation. On the other hand, being resident in the Northern (aOR 0.48, 95% CI: 0.29–0.78) and Northwestern regions (aOR 0.54, 95% CI: 0.36–0.80), belonging to a female headed household (aOR 0.69, 95% CI: 0.56–0.85) and being a working woman (aOR 0.66, 95% CI: 0.52–0.84) were associated with lower odds of utilizing PNC. Conclusion Factors associated with utilisation of PNC services operate at individual, household, community and health system/policy levels. Some of them can be ameliorated by targeted government interventions to improve utilisation of PNC services.

Epidemiological waves - types, drivers and modulators in the COVID-19 pandemic

Introduction: A discussion of 'waves' of the COVID-19 epidemic in different countries is a part of the national conversation for many, but there is no hard and fast means of delineating these waves in the available data and their connection to waves in the sense of mathematical epidemiology is only tenuous. Methods: We present an algorithm which processes a general time series to identify substantial, significant and sustained periods of increase in the value of the time series, which could reasonably be described as 'observed waves'. This provides an objective means of describing observed waves in time series. Results: The output of the algorithm as applied to epidemiological time series related to COVID-19 corresponds to visual intuition and expert opinion. Inspecting the results of individual countries shows how consecutive observed waves can differ greatly with respect to the case fatality ratio. Furthermore, in large countries, a more detailed analysis shows that consecutive observed waves have different geographical ranges. We also show how waves can be modulated by government interventions and find that early implementation of non-pharmaceutical interventions correlates with a reduced number of observed waves and reduced mortality burden in those waves. Conclusion: It is possible to identify observed waves of disease by algorithmic methods and the results can be fruitfully used to analyse the progression of the epidemic.

Resilience of countries to COVID-19 correlated with trust

We characterized > 150 countries’ resilience to COVID-19 as the nationwide decay rate of daily cases or deaths from peak levels. Resilience to COVID-19 varies by a factor of ~ 40 between countries for cases/capita and ~ 25 for deaths/capita. Trust within society is positively correlated with country-level resilience to COVID-19, as is the adaptive increase in stringency of government interventions when epidemic waves occur. By contrast, countries where governments maintain greater background stringency tend to have lower trust within society and tend to be less resilient. All countries where > 40% agree “most people can be trusted” achieve a near complete reduction of new cases and deaths, but so do several less-trusting societies. As the pandemic progressed, resilience tended to decline, as adaptive increases in stringency also declined. These results add to evidence that trust can improve resilience to epidemics and other unexpected disruptions, of which COVID-19 is unlikely to be the last.

Factors affecting the performance of South African municipal officials: stakeholders’ perspectives

Since the inception of the democratically elected post-apartheid government, South Africa has experienced growing numbers of protests about inadequate provision of basic municipal services. Recent studies have revealed that the poor performance of municipal officials contributes towards poor municipal service delivery. This article is based on a study which used qualitative key stakeholder interviews to analyse the performance of South African municipal officials, specifically in the delivery of services. It found that the following inter-related factors were responsible for the lack of performance: an unsupportive institutional environment, negative power struggles, over-regulation, political interference, a tense and bureaucratic environment, lack of coherent management systems, absence of a culture of excellence, poor skill utilisation, poor oversight mechanisms, weak capacity to engage in collaborations, and lack of trust between councillors from different political parties. The study concludes that for South African municipalities to meet their constitutional obligations to deliver optimal basic services to the people, the government must, inter alia, invest in building the capacity of municipal officials through the development of skills and other crucial local government interventions and transformations. The municipalities should also depoliticise local government and promote non-partisan appointment of municipal officials.

COVID-19 Vaccinations and the Volatility of Energy Companies in International Markets

The COVID-19 pandemic has elevated both the risk and volatility of energy companies. Can mass vaccinations restore stability within this sector? To answer this question, we investigate stock market data from fifty-eight countries from January 2020 to April 2021. We document that vaccination programs assist in decreasing the volatility of energy stocks around the world. The drop in volatility is statistically and economically significant and robust to many considerations. The observed phenomenon survives a broad battery of control variables; it is also independent of the employed regression model or the volatility measurement approach. Moreover, the effect is not driven by the dynamics of the pandemic itself or the associated government interventions. Finally, we find the influence of vaccinations on energy stock volatility to be more pronounced in developed markets rather than in emerging ones. Our findings bear clear practical implications: policy makers around the world should consider the essential role of vaccinations in the energy sector.

Promoting Green Behavioral Intentions of the Tourists for the Growth of Sustainable Tourism Development in the Sundarbans of Bangladesh

The Sundarbans, the single largest mangrove forest of the world is one of the prime tourism destinations of Bangladesh. Due to lack of awareness and proper planning, tourism is causing severe threat to the ecosystem of the Sundarbans. It is therefore utmost important to ensure that the natural environment of the Sundarbans doesn't deteriorate further. Promoting green tourism may be a viable way to achieve it. This study was designed to identify the ways to promote green (environment-friendly) behavior among the stakeholders, especially the tourists – traveling into the Sundarbans. A convenience sampling technique was used in the study that included both domestic and foreign tourists. A structured questionnaire was developed that incorporated 30 Likert-scale questions based on four variables, namely 'awareness program', 'incentive programs', 'interpretation' and 'government interventions'. The four variables and their corresponding items were developed in the light of extant literature and adopted based on the socio-cultural atmosphere of Bangladesh. The survey was conducted from October 2019 to February 2020 and 320 valid responses were obtained. Multiple regression analysis was employed to test the proposed research model. The result shows that out of four independent variables, government intervention and incentive programs are significantly influential factors in achieving the green behavior of the tourists. The study findings are aligned with the previous studies. The findings will provide guidelines to the tourism service providers, destination hosts, local communities, government bodies and policy makers in achieving green behavior of the tourists that in turn will yield sustainable tourism in the Sundarbans.

Numbers of close contacts of individuals infected with SARS-CoV-2 and their association with government intervention strategies

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.

Impact of Modelling Approach on the Estimation of Government Intervention Effects in COVID-19

The efficacy of government interventions in epidemic has become a hot subject since the onset of COVID-19. There is however much variation in the results quantifying the effects of interventions, which is partly related to the varying modelling approaches employed by existing studies. This paper therefore aims to examine how the choice of modelling approach would affect the estimation results of intervention effects, by experimenting with different modelling approaches on a same data set composed of the 500 most affected U.S. counties. We compare the most frequently used methods from the two classes of modelling approaches, which are Bayesian hierarchical model from the class of computational approach and difference-in-difference from the class of natural experimental approach. We find that computational methods are likely to produce larger estimates of intervention effects due to simultaneous voluntary behavioral changes. In contrast, natural experimental methods are more likely to extract the true effect of interventions. Among different difference-in-difference estimators, the two-way fixed effect estimator seems to be an efficient one. Our work can inform the methodological choice of future research on this topic, as well as more robust re-interpretation of existing works, to facilitate both future epidemic response plans and the science of public health.