Resilience and Sustainability in the Gulf Migration Regimes: Kafāla in the Era of Covid-19

The ongoing Covid-19 pandemic has strongly reaffirmed the critical importance of labor migration to the global economy, even as it has raised questions about the temporary migration programs responsible for much of this migration. In the Arab Gulf states–home to some of the world's highest proportions of migrants–the pandemic has highlighted critical structural weaknesses in the region's kafāla migration regimes. Drawing on two nationally representative surveys of Qatar's citizens and migrants conducted between October 2020 and June 2021, we argue that the Gulf's temporary migration regimes have shown resilience during the pandemic regarding flexibility, networks, and policies. However, Gulf states have gained this resilience at the expense of migrant workers, which threatens the sustainability of the kafāla in its current form. Nevertheless, we also identify key reforms undertaken in Qatar, which continued during the pandemic, and we find general acceptance of these reforms by citizens and business owners. Additionally, we find that Covid-19 has promoted recognition of the importance of migrant workers in the national labor supply, even if significant steps are still required to reduce migrant vulnerability. © 2023 Taylor & Francis Group, LLC.

CRC-PREVENT: Clinical validation trial to show expedited and diverse recruitment for the non-invasive RNA-FIT test that can detect advanced colorectal neoplasia with high sensitivity

Background: Prevailing methods for patient recruitment in large prospective studies can be time consuming, expensive, and introduce selection bias against patients with low health literacy or reduced access to healthcare. Previous clinical trials have reported low recruitment of women, minorities, and individuals who face socioeconomic barriers;a concern which has been exacerbated by the COVID-19 pandemic. Here we describe a novel recruitment strategy that helps to address healthcare disparities. This study will support a pre-market approval application to the FDA for a multi-factor RNA-FIT assay for detection of colorectal neoplasia in average-risk individuals between the ages of 45-75. Methods: A decentralized clinical trial (CRC-PREVENT) was launched through a digital campaign (https://www.colonscreeningstudy.com/;NCT04739722) after the RNA-FIT test system entered design-lock. Online advertisements were published on multiple social media sites and engagement with materials directed patients to an online screener. Participants who completed the screener were considered eligible for enrollment if they met CRC-PREVENT inclusion/ exclusion criteria and were willing to complete all components of the clinical trial, including providing a stool sample prior to an optical colonoscopy. Results: After 3 months of active enrollment, 51,588 individuals have engaged with digital advertisements and completed pre-screener surveys to determine eligibility. In total, 35,280 individuals were deemed eligible based on survey response, and 13,294 eligible individuals also expressed interest in the CRC-PREVENT clinical trial. Of these individuals, 48% were female and 34% were over the age of 60 years old. Regarding race, interested individuals directly represented the intended use population: 17% were Black or African American, 2.7% were Asian, and 1.3% were Native Hawaiian, Pacific Islander, American Indian, or Alaskan Native. With respect to ethnicity, 8.4% identified as Hispanic or Latinx. The decentralized approach also permitted access to individuals with socioeconomic healthcare inequities: 27% had income under $29,999 and 14% were on Medicaid. Individuals were derived from all 48 continental United States, and of those who reported their residential location, approximately 3% were from rural areas. Conclusions: Use of a decentralized recruitment strategy permitted highly successful enrollment in the face of challenges associated with COVID-19. With respect to race, ethnicity, socioeconomic status, and geography, all metrics represented significantly more diverse populations than observed in traditional clinical studies. Decentralized enrollment mitigated selection bias, and will result in data more reflective of the intended use population.

Short-Term Holt Smoothing Prediction Model of Daily COVID-19 Reported Cumulative Cases

COVID-19 is the most deadly respiratory diseases worldwide known so far. It is a real public health problem against which contingency measures such as social distancing and lock down are often used to decrease the number of cases when it increases exponentially. These measures along with their impacts are set based on knowledge about the propagation of the disease, in particular the daily reported new and total cases within a given country. To plan in advance efficient contingency measures in order to stop its rapid propagation and to mitigate a possible explosion of the active cases leading to an uncontrolled situation and a saturation of health structures, governments need to have an indication about the potential number of total cases during incoming days;prediction models such as SIR algorithm try to provide such a kind of prediction. However, ‘existing models like SIR are complex and consider many unrealistic parameters. This paper proposes, based on Holt’s smoothing method combined with a logarithmic function for cold start, a very simple short-term prediction of the daily total number of COVID-19 cases. Our experimental evaluation over various COVID-19 real-world datasets from different countries show that our model, particularly using a linear trend function, gives results with low error rates. We also show that our approach can be generalized to all countries around the world. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

NEUROCOVID: Experience of a Sub-Saharan African country, example of Senegal

Background and Aims: Initially barely affected by the COVID-19, the African continent suffered a second violent wave this winter. Neurological manifestations worldwide are increasingly reported, dominated by encephalitis, stroke and polyradiculoneuritis. We report the Senegalese experience of Neurocovid through a series of 9 patients. Methods: This is a prospective study of patients hospitalized in the neurology department of Fann. Were included patients who had neurological manifestations during or following an COVID-19 infection defined by a positive PCR or a recent infection with ELISA serology or typical chest imaging. Results: We collected 9 patients (6 men and 3 women), aged 7 to 80 years. Diagnoses were: 3 encephalitis, 4 polyradiculoneuritis, 1 hemorrhagic stroke and 1 chorea. 4 patients had comorbidities. The delay for neurological signs appearance was 11.1 days. A nasal swab was positive on 5/8 patients. Antibodies were found in all 3 negative patients. The LCR study showed hyperproteinorrachia in 7/9 patients. 5 patients underwent CT chest scan, showing ground glass opacities. Brain imaging was normal in 3 and pathological in 2, showing a parietal temporo hematoma fx1 in one and mesencephalic and parietal hypersignal in the other fx2 50% of patients with polyradiculoneuritis had an ENMG that showed an AIDP. One patient had an electroencephalogram that showed an overall slowing of the pattern with diffuse pseudoperiodic complexes fx3. Evolution was good for 6 patients but we noticed 3 deaths. [Formula presented] [Formula presented] [Formula presented] Conclusions: Neurological manifestations most often occur in post-infection. The creation of a multidisciplinary team will allow a better understanding of the sequel as of patients with COVID-19.