Ukraine's triple emergency: Food crisis amid conflicts and COVID-19 pandemic

TeleHelp Ukraine: A distributed international telemedicine response to the ongoing war

Background

Humanitarian crises frequently garner solidarity and robust volunteer recruitment among health care communities. However, a common obstacle is matching providers to those in need across geographic and other barriers. We examined the application of a decentralised governance strategy in establishing an emergency telemedicine response, TeleHelp Ukraine (THU).

Methods

Using a case study approach, we explored how global networking and technological advancements empower organisations to generate, access, disseminate, and utilise knowledge for sustainable health care delivery.

Results

Preliminary results suggest that a non-profit, decentralised model strengthened by robust team dynamics may optimise the distribution of clinical workload and scheduling procedures. Institutional and cultural diversity among health care providers and volunteers fosters the mobilisation of knowledge resources, synergistic collaboration, and tailored care standards that align with both provider and patient expectations. By integrating these diverse, distributed networks, a synergistic effect is achieved, combining effective learning mechanisms with intellectual capital.

Conclusions

Our study provides insights into the structure, implementation strategies, dissemination methodologies, and initial results of THU's operation. These findings may inform future emergency telemedicine responses in humanitarian scenarios, thereby reinforcing the practical implementation of health as a human right.

Spatiotemporal modeling of household's food insecurity levels in Ethiopia

The state of moderate and severe food insecurity in Ethiopia has not been significantly reduced for a long time due to cultural, natural, and manmade shocks, which cover most part of the country with considerable magnitude and have adverse effects on the health and economy. This temporal evolution of the wider geographic distribution of the food insecurity levels has not been investigated for the feeding culture and shocks effect in Ethiopia, though previous studies have indicated significant geographic distribution and related factors. In addition, the longtime zone-specific comprehensive drivers were not assessed. Therefore, this study focused on investigating the feeding culture-adjusted food insecurity levels (FCSL) and their evolutional sustainability across zones by identifying the factors causing each level of household's food insecurity tailored to a specific zone. In this study, Ethiopian socio-economic longitudinal data from years 2012, 2014, and 2016 with a sample size of 3835 households were analyzed. An ordinal spatiotemporal model with different interactions under empirical Bayes estimation was adopted, and the type III interaction with Markov random field was selected to reveal the evolution of FCSL sustainability across zones and find-out the causing factors of households to each level of food insecurity tailored to zone-level by analyzing the effects of diverse factors and shocks. The result reveals that a greater portion (52.07 %) of households' population is moderately and chronically food insecure. Basically, households living in neighboring zones have significantly similar food insecurity levels, and slight improvements were observed over time. This transition over time within neighboring zones, revealed that chronic food insecurity in neighboring zones has transited to moderate food insecurity, particularly in most of the northern and southwestern areas of Ethiopia. However, the interaction term showed that the change in food insecurity levels for households living in neighboring zones is similar at one time point, but the evolution is not sustainable. Therefore, working on major zone-specific factors, such as enhancing zone-level urbanization through improving market and road linkage to rural areas, education, employment, non-agricultural businesses, and promoting integrated farming by conserving soil with consideration of additional confounding factors, will bring change and can sustainably eradicate moderate and chronic food insecurity in zone households through controlling dependency ratios, shocks, and small land size farming. This study brings resilient, manageable, and zone-specific mitigation for households living in food-insecure and vulnerable zones.

Impact of COVID-19 on the Health of Migrant Children in the United States: From Policy to Practice

In this article, the authors provide an overview how the COVID-19 pandemic impacted the health and wellbeing of migrant children in conflict zones, in transit and post-settlement in the United States. In particular, the authors explore how policies implemented during the pandemic directly and indirectly affected migrant children and led to widening disparities in the aftermath of the pandemic. Given these circumstances, the authors provide recommendations for child health care providers caring for migrant children to mitigate and bolster resilience and health.

The spatial effects of the household's food insecurity levels in Ethiopia: by ordinal geo-additive model

Background

Food insecurity and vulnerability in Ethiopia are historical problems due to natural- and human-made disasters, which affect a wide range of areas at a higher magnitude with adverse effects on the overall health of households. In Ethiopia, the problem is wider with higher magnitude. Moreover, this geographical distribution of this challenge remains unexplored regarding the effects of cultures and shocks, despite previous case studies suggesting the effects of shocks and other factors. Hence, this study aims to assess the geographic distribution of corrected-food insecurity levels (FCSL) across zones and explore the comprehensive effects of diverse factors on each level of a household's food insecurity.

Method

This study analyzes three-term household-based panel data for years 2012, 2014, and 2016 with a total sample size of 11505 covering the all regional states of the country. An extended additive model, with empirical Bayes estimation by modeling both structured spatial effects using Markov random field or tensor product and unstructured effects using Gaussian, was adopted to assess the spatial distribution of FCSL across zones and to further explore the comprehensive effect of geographic, environmental, and socioeconomic factors on the locally adjusted measure.

Result

Despite a chronological decline, a substantial portion of Ethiopian households remains food insecure (25%) and vulnerable (27.08%). The Markov random field (MRF) model is the best fit based on GVC, revealing that 90.04% of the total variation is explained by the spatial effects. Most of the northern and south-western areas and south-east and north-west areas are hot spot zones of food insecurity and vulnerability in the country. Moreover, factors such as education, urbanization, having a job, fertilizer usage in cropping, sanitation, and farming livestock and crops have a significant influence on reducing a household's probability of being at higher food insecurity levels (insecurity and vulnerability), whereas shocks occurrence and small land size ownership have worsened it.

Conclusion

Chronically food insecure zones showed a strong cluster in the northern and south-western areas of the country, even though higher levels of household food insecurity in Ethiopia have shown a declining trend over the years. Therefore, in these areas, interventions addressing spatial structure factors, particularly urbanization, education, early marriage control, and job creation, along with controlling conflict and drought effect by food aid and selected coping strategies, and performing integrated farming by conserving land and the environment of zones can help to reduce a household's probability of being at higher food insecurity levels.

Household food insecurity levels in Ethiopia: quantile regression approach

Introduction

Numerous natural and man-made factors have afflicted Ethiopia, and millions of people have experienced food insecurity. The current cut-points of the WFP food consumption score (FCS) have limitations in measuring the food insecurity level of different feeding patterns due to the diversified culture of the society. The aim of this study is to adapt the WFP food security score cut-points corrected for the different feeding cultures of the society using effect-driven quantile clustering.

Method

The 2012, 2014, and 2016 Ethiopian socio-economic household-based panel data set with a sample size of 3,835 households and 42 variables were used. Longitudinal quantile regression with fixed individual-specific location-shift intercept of the free distribution covariance structure was adopted to identify major indicators that can cluster and level quantiles of the FCS.

Result

Household food insecurity is reduced through time across the quintiles of food security score distribution, mainly in the upper quantiles. The leveling based on effect-driven quantile clustering brings 35.5 and 49 as the FCS cut-points corrected for cultural diversity. This corrected FCS brings wider interval for food insecure households with the same interval range for vulnerable households, where the WFP FCS cut-points under estimate it by 7 score. Education level, employment, fertilizer usage, farming type, agricultural package, infrastructure-related factors, and environmental factors are found to be the significant contributing factors to food security. On the other hand, the age of the head of the household, dependency ratio, shock, and no irrigation in households make significant contributions to food insecurity. Moreover, households living in rural areas and farming crops on small lands are comparatively vulnerable and food insecure.

Conclusion

Measuring food insecurity in Ethiopia using the WFP FCS cut-off points underestimates households' food insecurity levels. Since the WFP FCS cut-points have universality and comparability limitations, there is a need for a universally accepted local threshold, corrected for local factors those resulted in different consumption patterns in the standardization of food security score. Accordingly, the quantile regression approach adjusts the WFP-FCS cut points by adjusting for local situations. Applying WFP cut-points will wrongly assign households on each level, so the proportion of households will be inflated for the security level and underestimated for the insecure level, and the influence of factors can also be wrongly recommended the food security score for the levels. The quantile clustering approach showed that cropping on a small land size would not bring about food security in Ethiopia. This favors the Ethiopian government initiative called integrated farming "ኩታ ገጠም እርሻ" which Ethiopia needs to develop and implement a system that fits and responds to this technology and infrastructure.