Corrigendum: Non-communicable disease care and management in two sites of the Cape Town Metro during the first wave of COVID-19: A rapid appraisal.

No abstract available.

Two months follow-up of patients with non-critical COVID-19 in Cape Town, South Africa.

BACKGROUND: Approximately 10% of coronavirus disease 2019 (COVID-19) patients will experience long COVID. There is no study of long COVID in mild COVID-19 patients in South Africa. This study aimed, firstly, to describe the prevalence of long COVID in mild COVID-19 patients in Cape Town, and, secondly, to document the impact of COVID-19 on patients' well-being, work, and their access to long COVID treatment. METHODS: In this retrospective cross-sectional study, a random sample of adults diagnosed with mild COVID-19 were called two months post-diagnosis. The participants telephonically completed a standardised survey describing their long COVID symptoms, missed workdays, and health-seeking behaviour. Medical records were reviewed for comorbidities, original COVID-19 symptoms, and treatment. RESULTS: It was found that 60% of patients with mild COVID-19 had ≥ 1 long COVID symptom, while 35% had ≥ 3 ongoing symptoms for two months. Dyspnoea and fatigue were the most common symptoms. The findings revealed that 52% of employed patients missed work and 25% of patients self-reported non-recovery from their COVID-19. Moreover, 24% of patients consulted a clinician for long COVID, but only 7% of patients received long COVID care in the public sector. Of the 17% of patients requiring additional help for long COVID, 56% were interested in assistance by text message or telephonic consultation. CONCLUSION: Over a half of mild COVID-19 patients experienced at least one long COVID symptom for two months and nearly 20% needed additional medical treatment. Very few patients utilised the public sector for long COVID treatment. There is a great need for long COVID treatment in public healthcare services and patients are receptive to remote care.

Non-communicable disease care and management in two sites of the Cape Town Metro during the first wave of COVID-19: A rapid appraisal.

BACKGROUND:  Non-communicable diseases (NCDs), including type-2 diabetes and hypertension, have been associated with increased morbidity and mortality rates because of coronavirus disease 2019 (COVID-19). Maintaining quality care for these conditions is important but data on the impact of COVID-19 on NCD care in South Africa are sparse. AIM:  This study aimed to assess the impact of COVID-19 on facility and community-based NCD care and management during the first COVID-19 wave. SETTING:  Two public health sector primary care sites in the Cape Town Metro, including a Community Orientated Primary Care (COPC) learning site. METHODS:  A rapid appraisal with convergent mixed-methods design, including semi-structured interviews with facility and community health workers (CHWs) (n = 20) and patients living with NCDs (n = 8), was used. Interviews were conducted in English and Afrikaans by qualified interviewers. Transcripts were analysed by thematic content analysis. Quantitative data of health facility attendance, chronic dispensing unit (CDU) prescriptions and routine diabetes control were sourced from the Provincial Health Data Centre and analysed descriptively. RESULTS:  Qualitative analysis revealed three themes: disruption (cancellation of services, fear of infection, stress and anxiety), service reorganisation (communication, home delivery of medication, CHW scope of work, risk stratification and change management) and outcomes (workload and morale, stigma, appreciation and impact on NCD control). There was a drop in primary care attendance and an increase in CDU prescriptions and uncontrolled diabetes. CONCLUSION:  This study described the service disruption together with rapid reorganisation and change management at primary care level during the first COVID-19 wave. The changes were strengthened by the COPC foundation in one of the study sites. The impact of COVID-19 on primary-level NCD care and management requires more investigation.

Reflections on epistemological aspects of artificial intelligence during the COVID-19 pandemic.

Artificial intelligence plays an important role and has been used by several countries as a health strategy in an attempt to understand, control and find a cure for the disease caused by Coronavirus. These intelligent systems can assist in accelerating the process of developing antivirals for Coronavirus and in predicting new variants of this virus. For this reason, much research on COVID-19 has been developed with the aim of contributing to new discoveries about the Coronavirus. However, there are some epistemological aspects about the use of AI in this pandemic period of Covid-19 that deserve to be discussed and need reflections. In this scenario, this article presents a reflection on the two epistemological aspects faced by the COVID-19 pandemic: (1) The epistemological aspect resulting from the use of patient data to fill the knowledge base of intelligent systems; (2) the epistemological problem arising from the dependence of health professionals on the results/diagnoses issued by intelligent systems. In addition, we present some epistemological challenges to be implemented in a pandemic period.