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Background: Although Namibia has made strides in improving the policy enabling environment, eradication of malnutrition is still elusive., Objective: This review was aimed at determining the extent to which food and nutrition-related policies in Namibia address malnutrition., Methods: This study used a qualitative approach by retrospectively analysing policy frameworks that address malnutrition in Namibia from 1991 to 2022. The analysis employed the policy triangle framework to elucidate the contextual factors, content, actors and process involved in the policy development. Moreover, a comparative analysis of Namibian policies and those of other southern African countries was undertaken., Results: The review showed that there is a considerable degree of coherence in policy goals and strategies to address malnutrition despite parallel coordination structures. Policy process involved limited consultations with local communities which might have jeopardised the formulation of community problem-tailored interventions, ownership and participation in policy implementation. There is a strong political commitment to the eradication of malnutrition in Namibia. The Office of the Prime Minister played a leading role in policy development. Influential actors such as the UN agencies elevated the nutrition agenda. Further, the Namibian policy framework was generally similar to those of other southern African countries., Conclusions: The review showed that Namibia has relevant and comprehensive policies to address malnutrition, however, contextual factors indicated high levels of malnutrition still exist in the communities. Further research is needed to understand the barriers and enablers to optimal nutrition for children under five years in Namibia., Competing Interests: Declaration of conflicting interestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

The degree to which elevated CO 2 concentrations (e[CO 2 ]) increase the amount of carbon (C) assimilated by vegetation plays a key role in climate change. However, due to the short-term nature of CO 2 enrichment experiments and the lack of reconciliation between different ecological scales, the effect of e[CO 2 ] on plant biomass stocks remains a major uncertainty in future climate projections. Here, we review the effect of e[CO 2 ] on plant biomass across multiple levels of ecological organization, scaling from physiological responses to changes in population-, community-, ecosystem-, and global-scale dynamics. We find that evidence for a sustained biomass response to e[CO 2 ] varies across ecological scales, leading to diverging conclusions about the responses of individuals, populations, communities, and ecosystems. While the distinct focus of every scale reveals new mechanisms driving biomass accumulation under e[CO 2 ], none of them provides a full picture of all relevant processes. For example, while physiological evidence suggests a possible long-term basis for increased biomass accumulation under e[CO 2 ] through sustained photosynthetic stimulation, population-scale evidence indicates that a possible e[CO 2 ]-induced increase in mortality rates might potentially outweigh the effect of increases in plant growth rates on biomass levels. Evidence at the global scale may indicate that e[CO 2 ] has contributed to increased biomass cover over recent decades, but due to the difficulty to disentangle the effect of e[CO 2 ] from a variety of climatic and land-use-related drivers of plant biomass stocks, it remains unclear whether nutrient limitations or other ecological mechanisms operating at finer scales will dampen the e[CO 2 ] effect over time. By exploring these discrepancies, we identify key research gaps in our understanding of the effect of e[CO 2 ] on plant biomass and highlight the need to integrate knowledge across scales of ecological organization so that large-scale modeling can represent the finer-scale mechanisms needed to constrain our understanding of future terrestrial C storage., (© 2022 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

Governments during the Covid-19 pandemic in response to the challenge of reaching as many of their citizens as quickly as possible have relied on the use of digital media communication. Various stakeholders, however, have questioned whether strategic use of digital communication by governments has been effective during the Covid-19 health crisis. We thematically analyzed a public online bi-country webinar and conducted a netnographic analysis of South African Health Minister Dr. Zweli Mkhize and Namibian Ministry of Health and Social Services Twitter accounts to evaluate the effectiveness of government digital communication during the Covid-19 pandemic. Stakeholders and social media analysis highlight that government digital communication has lacked engagement, falling short in assisting citizens to understand the effects of the Covid-19 pandemic. We highlight the shortcomings of governments simply transmitting information on channels built for dialogue, the digital divide limiting reach, as well as how limited engagement opens up opportunities for misinformation., Competing Interests: The authors declare no conflicts of interest., (© 2022 Policy Studies Organization.)

SARS-CoV-2 infections are now spreading across the world. Different measures were used by governments around the world to combat the spread of COVID-19. The efficacy of social distancing approaches in reducing the spread of COVID-19 in Ethiopia was investigated using geospatial technologies and the CHIME model. The COVID-19 response was predicted, measured, and compared after 25%, 75%, and 95% social distancing interventions in Ethiopia. Social distancing strategies flatten and delay the epidemic curve, according to the model findings. The model result shows that most new events and hospitalizations were avoided when social distancing measures were in effect. Social distancing can provide a critical time for increasing healthcare capability, and the research findings could assist policymakers in estimating the immediate number of resources required and planning for potential COVID-19 initiatives in Ethiopia., (© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2021.)

The plant economics spectrum hypothesizes a correlation among resource-use related traits along one single axis, which determines species' growth rates and their ecological filtering along resource gradients. This concept has been mostly investigated and shown in perennial species, but has rarely been tested in annual species. Annuals evade unfavorable seasons as seeds and thus may underlie different constraints, with consequences for interspecific trait-trait, trait-growth, and trait-environment relations. To test the hypotheses of the plant economics spectrum in annual species, we measured twelve resource-use related leaf and root traits in 30 winter annuals from Israel under controlled conditions. Traits and their coordinations were related to species' growth rates (for 19 species) and their distribution along a steep rainfall gradient. Contrary to the hypotheses of the plant economics spectrum, in the investigated annuals traits were correlated along two independent axes, one of structural traits and one of carbon gain traits. Consequently, species' growth rates were related to carbon gain traits, but independent from structural traits. Species' distribution along the rainfall gradient was unexpectedly neither associated with species' scores along the axes of carbon gain or structural traits nor with growth rate. Nevertheless, root traits were related with species' distribution, indicating that they are relevant for species' filtering along rainfall gradients in winter annuals. Overall, our results showed that the functional constraints hypothesized by the plant economics spectrum do not apply to winter annuals, leading to unexpected trait-growth and trait-rainfall relations. Our study thus cautions to generalize trait-based concepts and findings between life-history strategies. To predict responses to global change, trait-based concepts should be explicitly tested for different species groups., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Kurze, Engelbrecht, Bilton, Tielbörger and Álvarez-Cansino.)

The SARS-CoV-2 infections continue to increase in Namibia and globally. Assessing and mapping the COVID-19 risk zones and modeling the response of COVID-19 using different scenarios are very vital to help decision-makers to estimate the immediate number of resources needed and plan for future interventions of COVID-19 in the area of interest. This study is aimed to identify and map COVID-19 risk zones and to model future COVID-19 response of Namibia using geospatial technologies. Population density, current COVID-19 infections, and spatial interaction index were used as proxy data to identify the different COVID-19 risk zones of Namibia. COVID-19 Hospital Impact Model for Epidemics (CHIME) V1.1.5 tool was used to model future COVID-19 responses with mobility restrictions. Weights were assigned for each thematic layer and thematic layer classes using the Analytical Hierarchy Process (AHP) tool. Suitably ArcGIS overlay analysis was conducted to produce risk zones. Current COVID-19 infection and spatial mobility index were found to be the dominant and sensitive factors for risk zoning in Namibia. Six different COVID-19 risk zones were identified in the study area, namely highest, higher, high, low, lower, and lowest. Modeling result revealed that mobility reduction by 30% within the country had a notable effect on controlling COVID-19 spread: a flattening of the peak number of cases and delay to the peak number. The research output could help policy-makers to estimate the immediate number of resources needed and plan for future interventions of COVID-19 in Namibia, especially to assess the potential positive effects of mobility restriction., Competing Interests: Conflict of InterestThe authors declare that they have no conflict of interests., (© Indian National Academy of Engineering 2021.)

A reference range is an essential part of clinical laboratory test interpretation and patient care. The levels of total serum protein (TSP) are measured in sera to assess nutritional, liver, and kidney disorders. This study determined the TSP reference range with respect to gender, age, and region in Namibia. A retrospective cross-sectional study was conducted to determine the TSP reference range among 78,477 healthy participants within the ages of less than one year to more than 65 yrs in 14 regions of Namibia. The reference range of TSP was 51-91 g/L for females and 51-92 g/L for males. A reduced TSP range of 48.00-85.55 g/L (2.5-97.5 percentiles) was established at <1-5 years and increased towards adolescence. An uttermost range of 54-93 g/L was observed from 36-65 years of age. At the age >65 years; a steady decline in the reference range (51.00-89 g/L) was recorded. An upper TSP range of 53-92 g/L (2.5-97.5 percentiles) was detected in Erongo, Zambezi, Hardap, Kavango East, and a comparable trend was also seen in Omusati with a 54-91 g/L range. Meanwhile; a reduced TSP range of 50-89 g/L was identified in Ohangwena. This study showed that gender, age, and geographical location can impact TSP levels with a significant clinical difference ( p < 0.05) between each category.

Current generation wireless sensor routing algorithms and protocols have been designed based on a myopic routing approach, where the motes are assumed to have the same sensing and communication capabilities. Myopic routing is not a natural fit for the IoT, as it may lead to energy imbalance and subsequent short-lived sensor networks, routing the sensor readings over the most service-intensive sensor nodes, while leaving the least active nodes idle. This paper revisits the issue of energy efficiency in sensor networks to propose a clustering model where sensor devices' service delivery is mapped into an energy awareness model, used to design a clustering algorithm that finds service-aware clustering (SAC) configurations in IoT settings. The performance evaluation reveals the relative energy efficiency of the proposed SAC algorithm compared to related routing algorithms in terms of energy consumption, the sensor nodes' life span and its traffic engineering efficiency in terms of throughput and delay. These include the well-known low energy adaptive clustering hierarchy (LEACH) and LEACH-centralized (LEACH-C) algorithms, as well as the most recent algorithms, such as DECSA and MOCRN.