Can Domestic Food Production Provide Future Urban Populations with Food and Nutrition Security?—Insights from Bangladesh, Kenya and Uganda

Population growth and urbanization increasingly put pressure on our planet's availability of areas needed for food production. The dependencies on domestically produced food are increasingly judged favourable, following the consequences of the Ukrainian war, with escalating fuel and grain prices and less accessibilities to low-income groups. It is, however, unclear whether land is domestically available. Applying a food system approach, the main aim of this article is to investigate spatial foodsheds and theoretical self-sufficiency for food production needed to supply increasing future populations in a selection of cities, including estimates for Dhaka in Bangladesh, Nairobi in Kenya and Kampala in Uganda. The projected foodshed scenario areas for the years 2020 and 2050 are estimated for the production of three core products currently extensively produced and consumed in the three countries. They show that it is not possible to feed an ever-increasing urban population based on domestic production alone. International trade, new technological developments and new consumer demands for less area-intensive food production systems may give solutions to the immense challenge of feeding the world's population with nutritious food in 2050. However, to ensure fair and inclusive transition pathways for low-income groups: (1) affordability and accessibility of trade opportunities, technologies and products, (2) a common vision aiming for the SDGs, including SDG2: Zero hunger and SDG11: Sustainable Cities and Communities as well as (3) best practices in co-creation and cooperation with the most vulnerable urban and rural populations, are highly needed.

Critical Commentary: Beyond growth and density: Recentring the demographic drivers of urban health and risk in the global south

Debates within urban studies concerning the relationship between urbanisation and infectious disease focus on issues of urban population growth, density, migration and connectivity. However, an effective long-term risk and wellbeing agenda, without which the threat of future pandemics cannot be mitigated, must also take account of demographic forces and changes as critical drivers of transmission and mortality risk within and beyond cities. A better understanding of the dynamics of fertility, mortality and changing age structures – key determinants of urban decline/growth in addition to migration – provides the foundation upon which healthier cities and a healthy global urban system can be developed. The study of how basic demographic attributes and trends are distributed in space and how they interact with risks, including those of infectious disease, must be incorporated as a priority into a post-COVID-19 urban public health agenda. This perspective concurs with recent debates in urban studies emphasising the demographic drivers of urban change. Moreover, it raises critical questions about the microbial and environmental emphasis of much research on the interface of urban health and governance.

Disparities in exposure and accessibility to health: A Spatial Assessment of Covid 19 Pandemic Situation of South Bengal

Inequality and disparities of health is prevalent in a developing nation like India. The emergence of the Novel Corona virus has further aggravated this existing problem. The major issue that has been observed in dealing with the pandemic situation is the lack of facilities for testing and inadequate health infrastructure to support the huge population of this nation. This infrastructural deficiency has evidently become severe as we move away from the city areas. In this study, we have tried to assess this rural-urban disparity of health infrastructure in the settings of the COVID 19 pandemic situation. The study has been conducted to measure rural-urban disparities of eight districts i.e. Howrah, Hooghly, Kolkata, North 24 Parganas and South 24 Parganas concerning risk factors and access to health care infrastructure. To achieve the desired objectives, we have used a multidisciplinary technique incorporating statistical, GIS techniques, composite index with several aspects e.g., geographical coverage and sufficiency of COVID care and testing facilities (CCF, CTF), economic status of people, medical costs, and susceptibility to covid risk factors i.e., number of infected populations, and population density. A significant correlation between access to CCF and CTF and the proportion of urban inhabitants has been found, i.e., urban populations mostly enjoy better access to treatment and testing with dense CTFs and CCFs over space. The density and serviceability of care facilities over rural regions decrease with less urbanized areas. Urban areas are found to be at higher risk in terms of the number of active cases, population density. The study helps us to geo visualize the current COVID scenario of South Bengal in terms of regional disparities. This will help us identify the nearest testing and care facilities to any location within the study area and will be useful in mitigating infrastructural lacuna.

Analysis of the Chemistry of Municipal Wastewaters for Forecasting the Conditions of Urban Population

The quality of wastewater and the socioeconomic aspects of the life of the population are shown to be interrelated. It is proposed to use municipal wastewater to diagnose the health of the population, to assess the feeding preferences of city dwellers, the use of alcohol, tobacco, medicines, and drugs, to assess the exposure of the population to the effect of hazardous chemicals (PAH, pesticides, preserving agents, plasticizers, etc.), and to timely reveal deceases (including COVID-19). The authors proposed several biomarkers, which are recommended to use to monitor the water-resource system as a component of the urban ecosystem.

Koala conservation in South East Queensland: A grey literature review analysis

This grey literature review documents koala (Phascolarctos cinereus) conservation initiatives applied across 12 local government areas in South East Queensland, Australia. To overcome threats to koalas' survival, the grey literature indicates that local governments in this region focus on wildlife management solutions, wildlife signage, habitat restoration projects and koala awareness campaigns. Despite these measures, land clearing of koala habitat to cater for urban population growth combined with recent bushfires and floods have contributed to the decline of koalas in this region. Recommendations to enhance progress include greater usage of the grey literature in peer review work and further application of social marketing to encourage residents to uptake behaviors that can mitigate threats to koalas, including slowing down when driving in koala zones, participating in citizen science, and leashing dogs when walking in native bush areas. The need for collaborative efforts aimed at conserving the koala from potential extinction is indicated. This paper provides an approach that can be applied to track progress on coordinated efforts to conserve koalas.

Eliciting Opinions on Health Messaging During the COVID-19 Pandemic: Qualitative Survey Study.

BACKGROUND: Effective public health messaging has been necessary throughout the COVID-19 pandemic, but stakeholders have struggled to communicate critical information to the public, especially in different types of locations such as urban and rural areas. OBJECTIVE: This study aimed to identify opportunities to improve COVID-19 messages for community distribution in rural and urban settings and to summarize the findings to inform future messaging. METHODS: We purposively sampled by region (urban or rural) and participant type (general public or health care professional) to survey participants about their opinions on 4 COVID-19 health messages. We designed open-ended survey questions and analyzed the data using pragmatic health equity implementation science approaches. Following the qualitative analysis of the survey responses, we designed refined COVID-19 messages incorporating participant feedback and redistributed them via a short survey. RESULTS: In total, 67 participants consented and enrolled: 31 (46%) community participants from the rural Southeast Missouri Bootheel, 27 (40%) community participants from urban St Louis, and 9 (13%) health care professionals from St Louis. Overall, we found no qualitative differences between the responses of our urban and rural samples to the open-ended questions. Participants across groups wanted familiar COVID-19 protocols, personal choice in COVID-19 preventive behaviors, and clear source information. Health care professionals contextualized their suggestions within the specific needs of their patients. All groups suggested practices consistent with health-literate communications. We reached 83% (54/65) of the participants for message redistribution, and most had overwhelmingly positive responses to the refined messages. CONCLUSIONS: We suggest convenient methods for community involvement in the creation of health messages by using a brief web-based survey. We identified areas of improvement for future health messaging, such as reaffirming the preventive practices advertised early in a crisis, framing messages such that they allow for personal choice of preventive behavior, highlighting well-known source information, using plain language, and crafting messages that are applicable to the readers' circumstances.

Evaluating city-scale urban mobility restriction in Jakarta due to the COVID-19 pandemic: the impact on subjective wellbeing

The COVID-19 pandemic has forced cities worldwide to implement social distancing on a large scale and even lockdowns. City lockdowns are considered a public health policy to reduce virus spread and at the same time to protect vulnerable groups of the population. However, studying the implications of city lockdowns on urban populations’ mental and emotional wellbeing has been widely neglected. Using a case study of Indonesia’s capital and the largest metropolitan area of Jakarta, this study investigates the temporal dynamics of emotions experienced by the citizen during two months of city-scale lockdown. This paper uses Twitter text data as the source for emotional analysis with almost 9000 tweets. The study suggests that positive emotions were more common than negative texts across all periods under study, with lockdown acting as momentum for enhancing family gatherings and serving as a reminder of the importance of health, as the common positive emotions identified. The study provides evidence on the possibility of crowdsourcing data such as Twitter as an alternative source of data for urban analytics that allows researchers to understand the effect of activities and events in a certain location on its citizens.

Prediction of Urban Scale Expansion Based on Genetic Algorithm Optimized Neural Network Model

With the continuous development of urbanization, the urban population is becoming more and more dense, and the demand for land is becoming more and more tense. Urban expansion has become an indispensable part of urban development. This paper studies the optimization of neural network structure by genetic algorithm, puts forward the prediction model of urban scale expansion based on a genetic algorithm optimization neural network, and compares the performance of the model with the basic model. A genetic algorithm BP neural network (GA-BP) optimized by the genetic algorithm is used to shorten the running time of the algorithm and improve the prediction accuracy, but it is easy to fall into local solution. The genetic algorithm is improved by immune cloning algorithm, and the CGA-BP neural network model is established to obtain the global optimal solution. Compared with the BP neural network model and GA-BP neural network model, the CGA-BP neural network model converges faster, and the training times reach the error condition after 79 times, while the BP neural network model and GA-BP neural network model need 117 times and 100 times, respectively, and the fitness value corresponding to the number of iterations of the model is larger. Therefore, the CGA-BP neural network algorithm can make prediction more accurately and quickly and predict the expansion of urban scale through urban conditions.

Determining Equality of Infection Rates: A Spatial Analysis of Factors Associated with the Spread of COVID-19 in Barcelona, Spain

Since March 2020, the COVID-19 disease has become a global concern, and its concentration has been primarily in urban settings. Previous research suggests that multidimensional factors allow understanding the distribution of the disease but has limitations such as having nonhomogeneous units as the object of study, not incorporating changes in sanitary control measures over time or the absence of mobility variables. To overcome these shortcomings, we investigated the association between socioeconomic, demographic, and built environment factors with infection rates in the Metropolitan Area of Barcelona, one of the most compact and mixed-use environments in Europe. For this purpose, we use spatial regression models at five different stages that capture variations in sanitary control measures. Our results indicate that before the lockdown, infections were concentrated in high-income areas, but once it started the pattern shifted toward areas characterized by overcrowding, with more people who did not have the opportunity to telework, as well as nursing homes. Although commuting time also maintained a positive association with infections, the use of public transportation was not observed to have a direct impact. Contrary to what was speculated at the beginning of the pandemic, density was not shown to be a decisive factor in explaining infection rates;therefore, the results suggest keeping the focus on the quality of housing to avoid intrafamily infections but particularly in those where elderly dependents live. Likewise, public transportation can maintain its benefits for the most vulnerable urban populations as long as minimum safety measures are guaranteed in its interior.

Identify the natural and socio-economic influencing factors of the new coronavirus pneumonia（COVID-19） incidence rates in Chinese cities

This study explored the effects of both natural and socio-economic factors, such as city size and healthcare capacity, on the spreading of COVID-19 in China's urban population from January 1 to March 5, 2020. Several statistical models and machine learning methods were used to identify the key determinants of the incidence rate of COVID-19. Based on the interpretable machine learning framework, possible nonlinear relationships between incidences and key impact factors were explored. The results showed that the incidence rate of COVID-19 in cities was influenced by several factors simultaneously. Among the factors, the population inflow rate from Wuhan was the factor that showed the highest correlation coefficient（0.43）, followed by the population growth rate（0.38）. Population migration size, city size and healthcare capacity were the key influencing factors. Nonlinear relationships existed between the key influencing factors and incidence rates. To be specific, the inflow rate from Wuhan had a S-shaped relationship and reaches an asymptote after 2%;the population density had an approximately linear relationship;the per capita GDP showed an evident inverted U curve with the per capita GDP over 100,000 yuan as the inflection point. City development needs to pay more attention to population density control and economic growth in order to bring more health benefits.

Urbanization and COVID‐19 incidence: A cross‐country investigation: Papers and Proceedings

This paper investigates the determinants of the diffusion and intensity of the COVID‐19 at the country level, focusing on the role played by urban agglomeration, measured using three urban variables: percentage of the urban population, population density, and primacy. We estimate the influence of urban agglomeration on two outcome variables: cumulative number of cases and deaths per 100,000 inhabitants up to 31 December 2020, using both parametric and semiparametric models. We also explore possible spatial effects. The non‐linear effects of the urban variables on the intensity of the disease reveal non‐monotonous relationships, suggesting that it is the size of the urban system that is linked to a stronger incidence.Alternate :Este artículo investiga los determinantes de la difusión y la intensidad de COVID‐19 a nivel de país, centrándose en el papel que desempeña la aglomeración urbana, medida a través de tres variables urbanas: el porcentaje de población urbana, la densidad de población y la primacía. Se utilizaron modelos paramétricos y semiparamétricos para estimar la influencia de la aglomeración urbana en dos variables de resultado: el número acumulado de casos y de muertes por 100.000 habitantes hasta el 31 de diciembre de 2020. También se exploraron los posibles efectos espaciales. Los efectos no lineales de las variables urbanas sobre la intensidad de la enfermedad revelaron relaciones no monótonas, lo que sugiere que el tamaño del sistema urbano es lo que está vinculado a una mayor incidencia.Alternate :抄録本稿では、都市集積が果たす役割に焦点を当てて、3つの都市変数〔urban variable:都市人口の割合(パーセンテージ)、人口密度、首座都市性(primacy)〕を用いて測定して、国レベルでのCOVID‐19の拡散とその強度の決定要因を調査する。パラメトリックモデル及びセミパラメトリックモデルの両方を用いて、2020年12月31日までの住民10万人当たりの累積症例数と死亡数の2つの結果変数に対する都市集積の影響を推定した。また、空間効果も推定した。疾患の強度に対する都市変数の非線形効果は非単調関係を示したことから、発生率をより大きくするのは都市システムのサイズであることが示唆された。

Methodology for Prioritizing Best Practices Applied to the Sustainable Last Mile—The Case of a Brazilian Parcel Delivery Service Company

The ever-increasing impacts of the last mile delivery sector on the environment and the quality of life of the urban population, such as increased congestion, demand best practices to be incorporated by companies to reduce impacts such as emission of air pollutants and Greenhouse Gases (GHG) and depletion of natural resources, among others. However, a myriad of strategies has been developed for this purpose but there is a lack of methodologies that allow the choice of the best ones for a specific case. Therefore, this study looks for those best practices to be employed through an innovative methodology that consists of SWOT analysis (Strengths, Weaknesses, Opportunities, and Threats), a map of strategies of the delivery service, and using the Sustainability Balanced Scorecard (SBSC) and the Analytic Hierarchy Process (AHP), with the differential of considering the peculiarities of each company. The results applied in a Brazilian last mile delivery service company show that best practices such as route optimization, implementation of new infrastructure and business models for urban deliveries, and use of information systems for fleet tracking and monitoring contribute significantly to improving performance indicators and achieving the sector’s goal to become more sustainable, and especially meeting the Sustainable Development Goals (SDGs) 8, 9, 11, and 17.

The post-pandemic future of shrinking cities

Urban population loss is driven by a mix of natural population decline and negative net migration. Put simply, cities shrink when deaths outpace births and residents leave. Shock events, like pandemics or wars, ran exacerbate both. The uneven geographic and socio-spatial impacts oi· COYID-19 may reinforce existing downward urban demographic trajectories and even forge new shrinking cities. As the global death toll passes 1 million we examine demographic and socio-economic trends to contemplate the post-pandemic future oi· shrinking cities, reflect upon inequality and innovation across LIS cities and regions, and reaffirm five propositions for just and equitable planning in shrinking cities. Although we concentrate primarily on the American context, much of the discussion is applicable throughout the world due to the global nature of both the pandemic and urban shrinkage.

Ecosystem service measurement model for urban population clean water monitoring

Clean Ecosystem service measurement model for urban population clean water monitoring Clean water as one of the ecosystem services and also a protected natural asset provides important information about the availability of natural resources for humans in response to the impacts of climate change and overall ecosystem health. The emergence of the COVID-19 pandemic which was exacerbated by the emergence of low-pressure areas for piped clean water services (PAM water) increasingly shows that if humans destroy biodiversity, it will have implications for other life support systems including clean water. This study identifies aspects of quantity, continuity, and quality (called 3K) of clean water from the piping system in the eastern part of DKI Jakarta, especially in areas with low pressure water supply. Through the Research and Development method, the aim of the study is to build a new model for measuring ecosystem services in monitoring clean water for residents in urban areas. Until the end of the first semester of 2020, the results of the study showed that it was true that there were areas with low pressure, but statistically it was not proven to significantly affect the emergence of complaints in terms of quantity, continuity, and quality of water supply to the population, so more in-depth parameters are needed. regarding the parameters of small water complaints (quantity), dead water (continuity), and piped clean water quality.