Lockdown Strategies Research Articles

The prevalence and distribution of malaria in Mpumalanga Province before and during COVID-19 (2017 - 2022).

South Africa (SA) has committed to eliminating malaria by 2028. However, the initial target was set for 2023. Additionally, the ongoing COVID-19 pandemic and the emergence of drug and insecticide resistance have been identified as potential stumbling blocks in the achievement of this goal. The impact of COVID-19 on the prevalence and distribution of malaria in SA is unclear. To describe the trends and distribution of malaria before and during the pandemic and its associated lockdown strategies in one of the country's malaria-endemic provinces, Mpumalanga Province. A descriptive, retrospective and cross-sectional study was conducted using Mpumalanga provincial malaria case data extracted from the provincial District Health Information System 2. The impact of COVID-19 on the prevalence and distribution of malaria was assessed in Mpumalanga Province between 2017 and 2022 using descriptive trend analysis. Malaria cases before (2017 - 2019) and post- COVID-19 (2020 - 2022) were cross-tabulated using Stata version 17. We used χ2 tests to test for significant differences, set at p<0.05. During the study period, 25 380 malaria cases were reported, with the majority men (61%) >26 years old, with reported international travel, primarily to Mozambique. Limpopo Province (93%) accounted for most of the locally imported cases. Headaches and fever were the most common symptoms before and post COVID-19, while asymptomatic malaria carriage was higher during and post COVID (p<0.05). Prior to the pandemic reporting of the preferred treatment for uncomplicated malaria, Coartem use was at 53%, declining to 21% thereafter. Although COVID-19-related restrictions on human movement greatly reduced the malaria burden in Mpumalanga Province, the high-risk group (young mobile men) remained unchanged over the study period. Of concern were the marked reduction in the reporting of Coartem doses administered and the increased prevalence of asymptomatic carriage since 2020. The importation of malaria poses one of the biggest challenges to malaria elimination in Mpumalanga Province. This study highlighted the impact of COVID-19 and its related lockdown restrictions on the delivery of malaria health services in Mpumalanga Province. If malaria elimination is to be achieved, all aspects of the malaria programme must be strengthened urgently. Additionally, the health system and cross-border collaborations must also be strengthened.

Kolmogorov-Zurbenko filter coupled with machine learning to reveal multiple drivers of surface ozone pollution in China from 2015 to 2022

Near-surface ozone pollution is a significant concern in China. Its meteorological drivers are uncontrolled, stressing an urgent need to quantify the anthropogenic-driven components. This study employs explainable machine learning (ML) algorithms to predict ozone concentrations, emphasizing the anthropogenic-driven trends after accounting for meteorological effects. Results present that radiation is the most important meteorological factor affecting ozone pollution in the Yangtze River Delta (YRD), Pearl River Delta (PRD), and Sichuan Basin (SCB), while temperature is dominant for the North China Plain (NCP). Even at lower temperatures, stronger solar radiation can still lead to the accumulation of higher ozone concentrations. The anthropogenic-driven ozone concentration showed an upward trend in China, with an interannual growth rate of 2.61 μg/m3 a−1 from 2015 to 2022. Nonetheless, its rising trend experienced a post-2019 downturn, due to the COVID-19 lockdown and emission reduction strategies. It started to rise in 2022. Regionally, NCP has the highest ozone concentration, the SCB has the most pronounced increase in 2022, but the PRD has no noticeable variation and no significant seasonal change after 2019. As for precursor emissions, the urban areas in China are mostly located in the VOC-limited (volatile organic component) and transitional regimes, highlighting that VOC control is more cost-effective.

Assessing the impacts of vaccination and viral evolution in contact networks

A key lesson learned with COVID-19 is that public health measures were very different from country to country. In this study, we provide an analysis of epidemic dynamics using three well-known stochastic network models—small-world networks (Watts–Strogatz), random networks (Erdös–Rényi), and scale-free networks (Barabási–Albert)—to assess the impact of different viral strains, lockdown strategies, and vaccination campaigns. We highlight the significant role of highly connected nodes in the spread of infections, particularly within Barabási–Albert networks. These networks experienced earlier and higher peaks in infection rates, but ultimately had the lowest total number of infections, indicating their rapid transmission dynamics. We also found that intermittent lockdown strategies, particularly those with 7-day intervals, effectively reduce the total number of infections, serving as viable alternatives to prolonged continuous lockdowns. When simulating vaccination campaigns, we observed a bimodal distribution leading to two distinct outcomes: pandemic contraction and pandemic expansion. For WS and ER networks, rapid mass vaccination campaigns significantly reduced infection rates compared to slower campaigns; however, for BA networks, differences between vaccination strategies were minimal. To account for the evolution of a virus into a more transmissible strain, we modeled vaccination scenarios that varied vaccine efficacy against the wild-type virus and noted a decline in this efficacy over time against a second variant. Our results showed that vaccination coverage above 40% significantly flattened infection peaks for the wild-type virus, while at least 80% coverage was required to similarly reduce peaks for variant 2. Furthermore, the effect of vaccine efficacy on reducing the peak of variant 2 infection was minimal. Although vaccination strategies targeting hub nodes in scale-free networks did not substantially reduce the total number of infections, they were effective in increasing the probability of preventing pandemic outbreaks. These findings underscore the need to consider the network structure for effective pandemic control.

A Metric of Societal Burden Based on Virus Succession to Determine Economic Losses and Health Benefits of China's Lockdown Policies: Model Development and Validation.

The COVID-19 pandemic had a profound impact on the global health system and economic structure. Although the implementation of lockdown measures achieved notable success in curbing the spread of the pandemic, it concurrently incurred substantial socioeconomic costs. The objective of this study was to delineate an equilibrium between the economic losses and health benefits of lockdown measures, with the aim of identifying the optimal boundary conditions for implementing these measures at various pandemic phases. This study used a model to estimate the half-lives of the observed case fatality rates of different strains. It was based on global infection and death data collected by the World Health Organization and strain sequence time series data provided by Nextstrain. The connection between the health benefits and economic losses brought by lockdown measures was established through the calculation of disability-adjusted life years. Taking China's city lockdowns as an example, this study determined the cost-benefit boundary of various lockdown measures during the evolution of COVID-19. The study reveals a direct proportionality between economic losses due to lockdowns and the observed case fatality rates of virus strains, a relationship that holds true irrespective of population size or per capita economic output. As SARS-CoV-2 strains evolve and population immunity shifts, there has been a notable decrease in the observed case fatality rate over time, exhibiting a half-life of roughly 8 months. This decline in fatality rates may offset the health benefits of maintaining unchanged lockdown measures, given that the resultant economic losses might exceed the health benefits. The initial enforcement of lockdown in Wuhan led to significant health benefits. However, with the decline in the observed case fatality rate of the virus strains, the economic losses increasingly outweighed the health benefits. Consequently, it is essential to consistently refine and enhance lockdown strategies in accordance with the evolving fatality and infection rates of different virus strains, thereby optimizing outcomes in anticipation of future pandemics.

Impact of COVID-19 on Profession and Health of Female Sex Workers: Apprehension, Acquiescence, and Resilience.

In Surat city of Gujarat, India, female sex workers (FSW)-based targeted interventions (TI) and community-based organizations (CBO) have been functioning since 1998. To document the impact of the COVID-19 lockdown (March-May 2020) on FSWs and STI/RTI/HIV preventive measures provided through TI/CBOs in Surat city, sequential, explanatory mixed-methods design was used. We conducted a desk review of quarterly programmatic data (2018-2020) of four TIs and CBOs and interviewed of 221 FSWs to study pre- and post-lockdown socioeconomic conditions, engagement in sex work, health services during COVID-19 lockdown and coping strategies, followed by five focus group discussions of FSWs and TI/CBO project staff. Study identified four major themes: reasons for working as a FSW during COVID-19 lockdown, entry to sex work during or as a consequence of lockdown, exploitation of FSWs during lockdown, and challenges of TI and CBOs in service provision in pandemic situation. Number of new registrations and STI/RTI detection increased immediately after lockdown. TI/CBO and other NGOs working for women welfare must build financial independence by training them in microeconomics, savings, and entrepreneurship. TI/CBO staff must also include experts in finance or business, trained in emergency response. The presence of strong TI/CBO network facilitated prompt delivery of essential commodities and financial aid to FSWs. However, laboratory and screening services were hampered, which warrants need of introducing self-test kits. In backdrop of decrease in condom distribution, continuation of sex work during lockdown and disruption of routine HIV/STI/RTI screening facilities, our study also recommends intensified HIV/STI/RTI screening among FSWs.

HLA-B and C Expression Contributes to COVID-19 Disease Severity within a South African Cohort.

Globally, SARS-CoV-2 has negatively impacted many lives and industries due to its rapid spread, severe outcomes, and the need for the implementation of lockdown strategies across the world. SARS-CoV-2 disease severity varies among different populations. Host genetics have been associated with various diseases, and their ability to alter disease susceptibility and severity. In addition, Human Leukocyte Antigen (HLA) expression levels and alleles vary significantly among ethnic groups, which might impact the host's response to SARS-CoV-2. Our previous study highlighted that HLA-A might have an effect on COVID-19 disease severity across ethnicities. Therefore, in this study, we aim to examine the effect of HLA-B and C expression levels on COVID-19 disease severity. To achieve this, we used real-time PCR to measure the HLA mRNA expression levels of SARS-CoV-2-infected individuals from a South African cohort and compared them across ethnic groups, disease outcomes, gender, comorbidities, and age. Our results show (1) that the effect of HLA-B mRNA expression levels was associated with differences in disease severity when we compare symptomatic vs. asymptomatic (p < 0.0001). While HLA-C mRNA expression levels were not associated with COVID-19 disease severity. (2) In addition, we observed that HLA-B and HLA-C mRNA expression levels were significantly different between South African Black individuals and South African Indian individuals (p < 0.0001, p < 0.0001). HLA-B mRNA expression levels among symptomatic South African Black individuals were significantly higher than symptomatic South African Indian individuals (p < 0.0001). In addition, the HLA-B mRNA expression levels of symptomatic South African Black individuals were significantly higher than asymptomatic South African Black individuals (p > 0.0001). HLA-C mRNA expression levels among symptomatic South African Black individuals were significantly higher than among symptomatic South African Indian individuals (p = 0.0217). (3) HLA-C expression levels were significantly different between males and females (p = 0.0052). In addition, the HLA-C expression levels of asymptomatic males are higher than asymptomatic females (p = 0.0375). (4) HLA-B expression levels were significantly different between individuals with and without comorbidities (p = 0.0009). In addition, we observed a significant difference between individuals with no comorbidities and non-communicable diseases (p = 0.0034), in particular, hypertension (p = 0.0487). (5) HLA-B expression levels were significantly different between individuals between 26-35 and 56-65 years (p = 0.0380). Our work is expected to strengthen the understanding of the relationship between HLA and COVID-19 by providing insights into HLA-B and C expression levels across ethnic populations in South Africa among COVID-19-symptomatic and asymptomatic individuals. Our results highlight that HLA-B mRNA expression levels contribute to COVID-19 severity as well as variation in ethnicities associated with COVID-19. Further studies are needed to examine the effect of HLA expression levels across various ethnic groups with contributing factors.

Modeling COVID-19 spread using multi-agent simulation with small-world network approach

BackgroundThe rapid global spread of COVID-19 has seriously impacted people’s daily lives and the social economy while also posing a threat to their lives. The analysis of infectious disease transmission is of significant importance for the rational allocation of epidemic prevention and control resources, the management of public health emergencies, and the improvement of future public health systems.MethodsWe propose a spatiotemporal COVID-19 transmission model with a neighborhood as an agent unit and an urban spatial network with long and short edge connections. The spreading model includes a network of defined agent attributes, transformation rules, and social relations and a small world network representing agents’ social relations. Parameters for each stage are fitted by the Runge-Kutta method combined with the SEIR model. Using the NetLogo development platform, accurate dynamic simulations of the spatial and temporal evolution of the early epidemic were achieved.ResultsExperimental results demonstrate that the fitted curves from the four stages agree with actual data, with only a 12.27% difference between the average number of infected agents and the actual number of infected agents after simulating 1 hundred times. Additionally, the model simulates and compares different “city closure” scenarios. The results showed that implementing a ‘lockdown’ 10 days earlier would lead to the peak number of infections occurring 7 days earlier than in the normal scenario, with a reduction of 40.35% in the total number of infections.DiscussionOur methodology emphasizes the crucial role of timely epidemic interventions in curbing the spread of infectious diseases, notably in the predictive assessment and evaluation of lockdown strategies. Furthermore, this approach adeptly forecasts the influence of varying intervention timings on peak infection rates and total case numbers, accurately reflecting real-world virus transmission patterns. This highlights the importance of proactive measures in diminishing epidemic impacts. It furnishes a robust framework, empowering policymakers to refine epidemic response strategies based on a synthesis of predictive modeling and empirical data.

Understanding the relationship between stay-at-home measures and vaccine shortages: a conventional, heterogeneous, and fractional dynamic approach

In light of the global prevalence of a highly contagious respiratory disease, this study presents a novel approach to address the pressing and unanticipated issues by introducing a modified vaccination and lockdown-centered epidemic model. The rapid spread of the disease is attributed to viral transmissibility, the emergence of new strains (variants), lack of immunization, and human unawareness. This study aims to provide policymakers with crucial insights for making informed decisions regarding lockdown strategies, vaccine availability, and other control measures. The research adopts three types of models: deterministic, heterogeneous, and fractional-order dynamics, on both theoretical and numerical approaches. The heterogeneous network considers varying connectivity and interaction patterns among individuals, while the ABC fractional-order derivatives analyze the impact of integer-order control in different semi-groups. An extensive theoretical analysis is conducted to validate the proposed model. A comprehensive numerical investigation encompasses deterministic, stochastic, and ABC fractional-order derivatives, considering the combined effects of an effective vaccination program and non-pharmaceutical interventions, such as lockdowns and shutdowns. The findings of this research are expected to be valuable for policymakers in different countries, helping them implement dynamic strategies to control and eradicate the epidemic effectively.

An IoT model for supporting global governmental lockdown scenarios: investigating comparative lockdown strategies and assessing generic perception of pandemic response

ABSTRACT We propose an integrated IoT model to blend IoT technologies, neutrosophic theory and AHP to handle uncertain conditions of real-life situations and aid decision-makers with systematic and optimum decisions. In our case study, four ranked scenarios are assigned the appropriate IoT technology generated to support the government and competent authorities in the pandemic outbreak to prevent growing risks. Our study is based on the decision-makers’ judgments that need to be expanded with more experts in the various aspects of government and competent authorities. The integrated IoT model provides a balance between the restart of economic life and COVID-19 outbreaks.

Final Year Mathematics Students Perception of e-Learning and Instruction During the Covid-19 Era

The current trend of most tertiary teaching to reach out students in different modes such as distance, weekends and sandwich resorts largely to online system. The Covid-19 pandemic brought up various lock-down strategies in most countries. This allowed most universities such as Valley View University (a Premier Private University in Ghana, West Africa) to start with online lesson delivery modes to help maintain their academic calendar. The aim of this study was to investigate into the perception final year students and lecturers in the Mathematics Education department had on the Online Learning System during the Covid-19 pandemic lockdown era. The study adopted an explanatory investigation design through a sample size of 378 respondents comprising 36 lecturers and 342 students. Students’ and lecturers’ response to questionnaires put in a Likert Scale were investigated in numerous descriptive and inferential statistics. The results revealed that lecturers registered a higher positive perception of online learning than students. This variation was however not significant. Specifically, lecturers perceived an increased flexibility in online learning, with learners utilizing a wide range of learning sources. Student interest however decreased in terms of the absence of in person meetings, promotion of students learning, ensuring autonomous learning environment, the absentness of cooperative learning strategies and among others. It was recommended that universities who resort to online means of teaching and learning should resource teachers and learners with the necessary accoutrements to help sustain their interest and minimize stress of teaching and learning. Researchers are however encouraged to further investigate into other factors necessary to sustain learners’ and teachers’ interest in coping with online (e-learning) modes.

Inconsistent and Arbitrary Age-Based Policies During the First Wave of the COVID-19 Pandemic

ABSTRACT The COVID-19 pandemic has forced countries to issue public measures to address threats to the safety of citizens and the healthcare system. The role of chronological age in the ways in which different countries coped with the pandemic is particularly intriguing. Based on pool of purposely selected twenty-one countries, this article compares a variety of urgent public health policies that have been enforced during the first wave of the pandemic. It analyzes the ways in which countries introduced instructions related to older people and/or chronological age in relation to: Lockdown, exit and triage policies. It also examined whether the issue of long-term care settings (LTCS) received special attention in the primary guidelines developed in response to the lockdown and exit strategies. The analysis demonstrates inconsistencies within and across countries in the enactment and implementation of age-based measures. Moreover, it suggests that both acts of omission and commission based on age can be interpreted as ageist, arbitrary, not based on evidence, too inclusive, and offensive toward older people and neglectful of specific risk groups.

Health Behaviors of Albanian Students at the University of Medicine During the Coronavirus Disease 2019 Pandemic

Background: The coronavirus disease 2019 (COVID-19) pandemic has affected humanity in all life areas, particularly stress levels and mental health issues. Objectives: The present research aimed to explore the knowledge, stress level, social distancing, and mental health of the students at the University of Medicine in Albania during the COVID-19 pandemic. Methods: We conducted an anonymous online-based validated survey. We used the Perceived Stress Scale (PSS10) and the perception of COVID-19’s impact (PCI) on well-being. The study’s inclusion criteria included having access to the Internet and being a student at the University of Medicine in Tirana, Albania. We used the statistical package SPSS 26.0 in this study. To analyze numeric variables, we used descriptive statistics and the chi-square test to analyze cross-tabulations of the survey response data for categorical variables. Results: Out of 521 students participating in our study (median age = 20 (1.3) years), 484 (92.9%) were female, and 37 (7.1%) were male; 62.4% had an adequate understanding of the transmission ways of COVID-19 (P = 0.0002); 16.8% of the students reported that social distancing had a significant impact on their psychological status, while 6.33% reported a moderate impact, with a statistically significant difference between the two groups (P = 0.0001). Concerning the students’ approach to trusted sources of information during the COVID-19 pandemic, 85.4% reported that they trusted information from friends, 11.1% from the World Health Organization (WHO), and 2.1% from the government (P = 0.0001). We observed a positive correlation according to Pearson chi-square and the likelihood ratio tests between treatment for health problems and health risks of the COVID-19 pandemic (P = 0.0041); 4.4% of students have reported being treated for mental health issues during the COVID-19-related quarantine period (P = 0.0002). Conclusions: Future lockdown strategies should consider the detrimental effects on student mental health. Based on the findings of our study, the COVID-19 pandemic caused significant distress among students. Universities should also adopt a creative and supportive approach to encourage and tackle students’ mental health problems during a pandemic.

Spatiotemporal Transmission Model to Simulate an Interregional Epidemic Spreading

Infectious disease spread is a spatiotemporal process with significant regional differences that can be affected by multiple factors, such as human mobility and manner of contact. From a geographical perspective, the simulation and analysis of an epidemic can promote an understanding of the contagion mechanism and lead to an accurate prediction of its future trends. The existing methods fail to consider the mutual feedback mechanism of heterogeneities between the interregional population interaction and the regional transmission conditions (e.g., contact probability and the effective reproduction number). This disadvantage oversimplifies the transmission process and reduces the accuracy of the simulation results. To fill this gap, a general model considering the spatiotemporal characteristics is proposed, which includes compartment modeling of population categories, flow interaction modeling of population movements, and spatial spread modeling of an infectious disease. Furthermore, the correctness of a theoretical hypothesis for modeling and prediction accuracy of this model was tested with a synthetic data set and a real-world COVID-19 data set in China, respectively. The theoretical contribution of this article was to verify that the interplay of multiple types of geospatial heterogeneities dramatically influences the spatial spread of infectious disease. This model provides an effective method for solving infectious disease simulation problems involving dynamic, complex spatiotemporal processes of geographical elements, such as optimization of lockdown strategies, analyses of the medical resource carrying capacity, and risk assessment of herd immunity from the perspective of geography. Key Words: geospatial heterogeneities, health geography, interregional population interaction, spatiotemporal analysis, transmission modeling.

All lockdowns are not equal: Reducing epidemic impact through evolutionary computation

The impact of different lockdown strategies upon the total number of infections in an epidemic are evaluated for two models of infection: one in which the disease confers permanent immunity, and one in which it does not. The strategies are based upon the proportion of the population infected at a time in order to trigger lockdown, combined with the proportion of interactions removed during lockdown. The population, its interactions, and the relative strengths of those interactions are stored in a weighted contact network, from which edges are removed during lockdown. These edges are selected using an evolutionary algorithm (EA) designed to minimize total infections. Using the EA to select edges significantly reduces total infections in comparison to random selection. In fact, the EA results for the least strict conditions were similar or better to the random results for the most strict conditions, showing that a judicious choice of restrictions during lockdown has the greatest effect on reducing infections. Further, when using the most strict rules a smaller proportion of interactions can be removed to obtain similar or better results in comparison to removing a higher proportion of interactions for less strict rules.

The Influence of Density and Mixed Land Use on The Spread of Covid-19 in Surakarta City

Covid-19 has a significant risk of spreading in urban areas because of the aglomeration of built-up areas and people. It frequently contains a mix of land uses and is accessible to urban amenities. Due to the area’s extensive usage of mixed land uses, it is better able to provide internal urban services on its own. Greater use of area lockdown and social separation strategies could result from this situation. The most populous city in the province of Central Java, Surakarta, has a significant risk of contracting COVID-19. The purpose of this study is to evaluate the impact of density and levels of mixed land use on the Covid-19 distribution in Surakarta City.Population density is used to calculate density. The entropy index approach was used to measure the amount of mixed land use. It is a method for calculating the balance between each form of land use. The availability of current land use data being processed by the spatial analysis with the Arc GIS application provided help for the analysis. Additionally, it makes use of information on Covid-19 cases in relation to the general populace that is supplied by the Surakarta Municipality. The relationship between mixed land use and Covid-19 risk was analyzed using a linear regression approach. The study’s findings indicated a minor influence between density and the spread of COVID-19. Meanwhile, the level of mixed land use does not influence the spread of the Covid-19 virus in Surakarta City.

The effectiveness of vaccination, testing, and lockdown strategies against COVID-19

The ability of various policy activities to reduce the reproduction rate of the COVID-19 disease is widely discussed. Using a stringency index that comprises a variety of lockdown levels, such as school and workplace closures, we analyze the effectiveness of government restrictions. At the same time, we investigate the capacity of a range of lockdown measures to lower the reproduction rate by considering vaccination rates and testing strategies. By including all three components in an SIR (Susceptible, Infected, Recovery) model, we show that a general and comprehensive test strategy is instrumental in reducing the spread of COVID-19. The empirical study demonstrates that testing and isolation represent a highly effective and preferable approach towards overcoming the pandemic, in particular until vaccination rates have risen to the point of herd immunity.

Stochastic epidemic spreading: not all super-spreading processes are born equal, neither all lockdown strategies

We consider viral spreading processes, such as pandemics, in finite networks. For such processes, we propose and analyze a new model which combines two stochastic functions in the spreading intensity of a node, and accounts for two types of super-spreading. The first reflects personal properties of each node and the second reflects occasional spreads in the network. Consequently, studying the spreading dynamics requires the analysis of a stochastic process consisting of those two functions which drastically differ in their dynamics. One (personal) is biasly-modified throughout the process as infected nodes” leave the game” and the distribution of the susceptible population changes. The second (occasional) remains constant throughout the process. We show that the mix between these functions affects dramatically the threshold for the end of the spread (known as the Herd Immunity Threshold, or HIT). We address operational aspects and examine the effectiveness of control mechanisms that restrict the interaction among the population in order to suppress the spread (e.g. lockdowns). We reveal and establish that although different policies might have similar immediate impacts, not all lockdowns are “born equal”, and may drastically differ on the long-term impact: While some reduce the HIT, others may be counter-productive in the long-run and, perhaps surprisingly, increase the HIT.

Nearly mobile: pandemic im/mobilities and lockdown strategies amongst Asian migrant professionals in England

ABSTRACT This article proposes ‘nearly mobile’ as a productive concept to illustrate the im/mobility experiences amongst Asian skilled migrants in England during a global health crisis. The concept of ‘nearly mobile’ describes how mobility practices and aspirations have been heavily restricted during national lockdowns, while still remaining fluid and relational, with both debilitating and empowering potentials. The ambiguity of ‘nearly’ offers both frustration and hope, when the desired ‘mobility as normal’ seems just out of reach. The concept of 'nearly mobile' offers two main dimensions. First, it highlights how migrants navigate through ‘shock precarities’ by safe-zoning – utilising and spatialising voluntary immobility to create unique work and living spaces based on daily assessments of risk and responsibility. Second, ‘nearly mobile’ reflects a continuous yearning for a return to normality, where forecasting and imagining become practical ways of seizing opportunities that emerge amidst crisis and uncertainty. We propose 'nearly mobile' as a productive framework for revaluing im/mobility in times of rising localism, protectionism, and the normalisation of transnational biopolitical regimes, which underpin a possible ‘new normal’ beyond the pandemic.

Salary Stoppage amidst COVID-19 Lockdown and Coping Strategies by Members of the Academic Staff Union of Universities (ASUU) in Nigeria

Salary Stoppage amidst COVID-19 Lockdown and Coping Strategies by Members of the Academic Staff Union of Universities (ASUU) in Nigeria

The Threat of COVID-19 on Food Security: A Modelling Perspective of Scenarios in the Informal Settlements in Windhoek

Due to the heterogeneity among households across locations, predicting the impacts of stay-at-home mitigation and lockdown strategies for COVID-19 control is crucial. In this study, we quantitatively assessed the effects of the Namibia government’s lockdown control measures on food insecurity in urban informal settlements with a focus on Windhoek, Namibia. We developed three types of conditional regression models to predict food insecurity prevalence (FIP) scenarios incorporating household frequency of food purchase (FFP) as the impacting factor, based on the Hungry Cities Food Matrix. Empirical data were derived from the 2017 African Food Security Urban Network (AFSUN) Windhoek study and applied univariate probit and bivariate partial observability models to postulate the relation between food insecurity and FFP within the context of stay-at-home disease mitigation strategy. The findings showed that FFP was positively correlated with the prevalence of food insecurity (r = 0.057, 95% CI: 0.0394, 0.085). Daily purchases portrayed a survivalist behaviour and were associated with increased food insecurity (coeff = 0.076, p = 0.05). Only those who were purchasing food twice monthly were significantly associated with reduced food insecurity (coeff = −0.201, p = 0.001). Those households in informal settlements were severely impacted by food insecurity (coeff = 0.909, p-value = 0.007). We conclude that public health compliance should precede with cash or food support to poor households in balance with the need for long-term placement of control measures to fully contain COVID-19 or related infectious diseases.