scholarly journals Initiation of contact tracing for Covid-19 at an academic institution for health science: initial experiences

2020 ◽  
Vol 10 (3) ◽  
pp. 109-110
Author(s):  
Rajan Paudel ◽  
Dipak Prasad Upadhyaya
Keyword(s):  
Information Flow ◽  
Health Workers ◽  
Task Shifting ◽  
Health Science ◽  
Contact Tracing ◽  
Resource Limited Settings ◽  
Resource Limited ◽  
Rural And Urban ◽  
Effective Contact ◽  
Different Parts

Transmission of COVID-19 cases has been found in clusters and sporadic form in different parts of Nepal, which swiftly strained the healthcare system. Contact tracing is a strategy to prevent further transmission of the COVID-19. It reduces the overwhelming burden in a health system. Academic institutions are the best alternative in contact tracing, not only in terms of task shifting but their training in epidemiology and research also best suits them. Besides, they can also train the health workers assigned for contact tracing in rural and urban settings. Multi-sectoral involvement from academia, community health workers, and effective information flow are instrumental for effective contact tracing in resource-limited settings.

scholarly journals COVID-19 control strategies and intervention effects in resource limited settings: A modeling study

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252570
Author(s):  
Kiran Raj Pandey ◽  
Anup Subedee ◽  
Bishesh Khanal ◽  
Bhagawan Koirala
Keyword(s):  
Control Strategies ◽  
Case Finding ◽  
Contact Tracing ◽  
Active Case Finding ◽  
Resource Limited Settings ◽  
Peak Demand ◽  
Active Case ◽  
Resource Limited ◽  
Base Scenario ◽  
Annual Mortality

Introduction Many countries with weaker health systems are struggling to put together a coherent strategy against the COVID-19 epidemic. We explored COVID-19 control strategies that could offer the greatest benefit in resource limited settings. Methods Using an age-structured SEIR model, we explored the effects of COVID-19 control interventions–a lockdown, physical distancing measures, and active case finding (testing and isolation, contact tracing and quarantine)–implemented individually and in combination to control a hypothetical COVID-19 epidemic in Kathmandu (population 2.6 million), Nepal. Results A month-long lockdown will delay peak demand for hospital beds by 36 days, as compared to a base scenario of no intervention (peak demand at 108 days (IQR 97-119); a 2 month long lockdown will delay it by 74 days, without any difference in annual mortality, or healthcare demand volume. Year-long physical distancing measures will reduce peak demand to 36% (IQR 23%-46%) and annual morality to 67% (IQR 48%-77%) of base scenario. Following a month long lockdown with ongoing physical distancing measures and an active case finding intervention that detects 5% of the daily infection burden could reduce projected morality and peak demand by more than 99%. Conclusion Limited resource settings are best served by a combination of early and aggressive case finding with ongoing physical distancing measures to control the COVID-19 epidemic. A lockdown may be helpful until combination interventions can be put in place but is unlikely to reduce annual mortality or healthcare demand.

scholarly journals Maternal, Newborn, and Child Survival (MNCS) Training Package for Frontline Health Workers in Resource-Limited Settings

MedEdPORTAL ◽  
2014 ◽  
Vol 10 (1) ◽  
Author(s):  
Maya Fehling ◽  
Brett Nelson ◽  
Roy Ahn ◽  
Melody Eckardt ◽  
Margaret Tiernan ◽  
...  
Keyword(s):  
Health Workers ◽  
Child Survival ◽  
Resource Limited Settings ◽  
Training Package ◽  
Frontline Health Workers ◽  
Resource Limited

scholarly journals Review of Current COVID-19 Diagnostics and Opportunities for Further Development

2021 ◽  
Vol 8 ◽  
Author(s):  
Yan Mardian ◽  
Herman Kosasih ◽  
Muhammad Karyana ◽  
Aaron Neal ◽  
Chuen-Yen Lau
Keyword(s):  
Critical Role ◽  
False Negative ◽  
Nucleic Acid Amplification ◽  
Detection Methods ◽  
Contact Tracing ◽  
Diagnostic Tools ◽  
Rt Pcr ◽  
Resource Limited Settings ◽  
Technical Errors ◽  
Resource Limited

Diagnostic testing plays a critical role in addressing the coronavirus disease 2019 (COVID-19) pandemic, caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Rapid and accurate diagnostic tests are imperative for identifying and managing infected individuals, contact tracing, epidemiologic characterization, and public health decision making. Laboratory testing may be performed based on symptomatic presentation or for screening of asymptomatic people. Confirmation of SARS-CoV-2 infection is typically by nucleic acid amplification tests (NAAT), which requires specialized equipment and training and may be particularly challenging in resource-limited settings. NAAT may give false-negative results due to timing of sample collection relative to infection, improper sampling of respiratory specimens, inadequate preservation of samples, and technical limitations; false-positives may occur due to technical errors, particularly contamination during the manual real-time polymerase chain reaction (RT-PCR) process. Thus, clinical presentation, contact history and contemporary phyloepidemiology must be considered when interpreting results. Several sample-to-answer platforms, including high-throughput systems and Point of Care (PoC) assays, have been developed to increase testing capacity and decrease technical errors. Alternatives to RT-PCR assay, such as other RNA detection methods and antigen tests may be appropriate for certain situations, such as resource-limited settings. While sequencing is important to monitor on-going evolution of the SARS-CoV-2 genome, antibody assays are useful for epidemiologic purposes. The ever-expanding assortment of tests, with varying clinical utility, performance requirements, and limitations, merits comparative evaluation. We herein provide a comprehensive review of currently available COVID-19 diagnostics, exploring their pros and cons as well as appropriate indications. Strategies to further optimize safety, speed, and ease of SARS-CoV-2 testing without compromising accuracy are suggested. Access to scalable diagnostic tools and continued technologic advances, including machine learning and smartphone integration, will facilitate control of the current pandemic as well as preparedness for the next one.

scholarly journals COVID-19 Control Strategies and Intervention Effects in Resource Limited Settings: A Modeling Study

2020 ◽  
Author(s):  
Kiran Raj Pandey ◽  
Anup Subedee ◽  
Bishesh Khanal ◽  
Bhagawan Koirala
Keyword(s):  
Control Strategies ◽  
Case Finding ◽  
Contact Tracing ◽  
Active Case Finding ◽  
Resource Limited Settings ◽  
Peak Demand ◽  
Active Case ◽  
Resource Limited ◽  
Base Scenario ◽  
Annual Mortality

ABSTRACTBackgroundMany countries with weaker health systems are struggling to put together a coherent strategy against the COVID-19 epidemic. We explored COVID-19 control strategies that could offer the greatest benefit in resource limited settings.MethodsUsing an age-structured SEIR model, we explored the effects of COVID-19 control interventions--a lockdown, physical distancing measures, and active case finding (testing and isolation, contact tracing and quarantine)-- implemented individually and in combination to control a hypothetical COVID-19 epidemic in Kathmandu (population 2.6 million), Nepal.ResultsA month-long lockdown that is currently in place in Nepal will delay peak demand for hospital beds by 36 days, as compared to a base scenario of no interventions (peak demand at 108 days (Inter-Quartile Range IQR 97–119); a 2 month long lockdown will delay it by 74 days, without any difference in annual mortality, or healthcare demand volume. Year-long physical distancing measures will reduce peak demand to 36% (IQR 23%-46%) and annual morality to 67% (IQR 48%-77%) of base scenario. Following a month long lockdown with ongoing physical distancing measures and an active case finding intervention that detects 5% of the daily infection burden could reduce projected morality and peak demand by more than 99%.InterpretationLimited resources settings are best served by a combination of early and aggressive case finding with ongoing physical distancing measures to control the COVID-19 epidemic. A lockdown may be helpful until combination interventions can be put in place but is unlikely to reduce annual mortality or healthcare demand.

scholarly journals Point of Care Diagnostics for HIV in Resource Limited Settings: An Overview

Medicina ◽  
2018 ◽  
Vol 54 (1) ◽  
pp. 3 ◽  
Author(s):  
Sello Manoto ◽  
Masixole Lugongolo ◽  
Ureshnie Govender ◽  
Patience Mthunzi-Kufa
Keyword(s):  
Viral Load ◽  
Health Workers ◽  
Point Of Care ◽  
Hiv Diagnosis ◽  
Hiv Viral Load ◽  
Resource Limited Settings ◽  
Art Initiation ◽  
Resource Limited ◽  
Timely Access ◽  
Access To Medical Care

Human immunodeficiency virus (HIV) is a global health problem. Early diagnosis, rapid antiretroviral therapy (ART) initiation and monitoring of viral load are the key strategies for effective HIV management. Many people in resource limited settings where timely access to medical care is a challenge and healthcare infrastructure is poor have no access to laboratory facilities and diagnosis is dependent on the presence of point of care (POC) devices. POC instruments have shown to be easy to operate, maintain and transport and can easily be operated by less skilled health workers. Additionally, POC tests do not require laboratory technicians to operate. POC devices have resulted in a growing number of people testing for HIV and thereby receiving treatment early. In recent years, there has been great improvement in the development of POC technologies for early HIV diagnosis, HIV viral load and cluster of differentiation 4 (CD4) measurement. This review discusses POC technologies that are currently available and in the pipeline for diagnosing and monitoring HIV. We also give an overview of the technical and commercialization challenges in POC diagnostics for HIV.

Global Health: Pediatric Neurology

2018 ◽  
Vol 38 (02) ◽  
pp. 200-207 ◽  
Author(s):  
Ornella Ciccone ◽  
Archana Patel ◽  
David Bearden
Keyword(s):  
Global Health ◽  
Health Workers ◽  
Epidemiologic Studies ◽  
Resource Limited Settings ◽  
Optimal Care ◽  
Resource Limited ◽  
Neurologic Disorders ◽  
Trained Personnel ◽  
Diagnostic Technology ◽  
Physician Extenders

AbstractNeurologic disorders contribute significantly to both morbidity and mortality among children in resource-limited settings, but there are a few succinct studies summarizing the epidemiology of neurologic disorders in these settings. A review of available literature was performed to identify data on the prevalence, etiology, outcomes, and treatment of neurologic disorders in children in resource-limited settings. The burden of neurologic disorders in children is high in resource-limited settings. Barriers to optimal care include lack of trained personnel, limited access to diagnostic technology, and limited availability of drugs used to treat common conditions. Several solutions have been suggested to deal with these challenges including increased collaborations to train neurologists willing to practice in resource-limited settings and increased training of physician extenders or community health workers. Further studies are necessary to improve our understanding of the epidemiology of neurologic disorders in resource-limited settings. Future epidemiologic studies should incorporate multiple countries in resource-limited settings and utilize standardized definitions and methodologies to enable comparison across regions.

scholarly journals Towards AI-Enabled Multimodal Diagnostics and Management of COVID-19 and Comorbidities in Resource-Limited Settings

Informatics ◽  
2021 ◽  
Vol 8 (4) ◽  
pp. 63
Author(s):  
Olawande Daramola ◽  
Peter Nyasulu ◽  
Tivani Mashamba-Thompson ◽  
Thomas Moser ◽  
Sean Broomhead ◽  
...  
Keyword(s):  
Point Of Care ◽  
Low Cost ◽  
Personal Data ◽  
Disease Diagnosis ◽  
Careful Consideration ◽  
Diagnostic Methods ◽  
Contact Tracing ◽  
Patient Treatment ◽  
Resource Limited Settings ◽  
Resource Limited

A conceptual artificial intelligence (AI)-enabled framework is presented in this study involving triangulation of various diagnostic methods for management of coronavirus disease 2019 (COVID-19) and its associated comorbidities in resource-limited settings (RLS). The proposed AI-enabled framework will afford capabilities to harness low-cost polymerase chain reaction (PCR)-based molecular diagnostics, radiological image-based assessments, and end-user provided information for the detection of COVID-19 cases and management of symptomatic patients. It will support self-data capture, clinical risk stratification, explanation-based intelligent recommendations for patient triage, disease diagnosis, patient treatment, contact tracing, and case management. This will enable communication with end-users in local languages through cheap and accessible means, such as WhatsApp/Telegram, social media, and SMS, with careful consideration of the need for personal data protection. The objective of the AI-enabled framework is to leverage multimodal diagnostics of COVID-19 and associated comorbidities in RLS for the diagnosis and management of COVID-19 cases and general support for pandemic recovery. We intend to test the feasibility of implementing the proposed framework through community engagement in sub-Saharan African (SSA) countries where many people are living with pre-existing comorbidities. A multimodal approach to disease diagnostics enabling access to point-of-care testing is required to reduce fragmentation of essential services across the continuum of COVID-19 care.

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