Proposed Algorithm for Integrated Management of TB-SARS-CoV-2 Co-Infection in a TB-Endemic Country.

Ni Made Mertaniasih, Soedarsono Soedarsono, Tiffany Tiara Pakasi, Zakiyathun Nuha, Manabu Ato

Abstract read

In one paragraph

Article in Tropical medicine and infectious disease, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

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0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Ni Made MertaniasihDepartment of Medical Microbiology, Faculty of Medicine, Universitas Airlangga, Surabaya 60131, Indonesia.ORCID 0000-0002-0594-2385

Soedarsono SoedarsonoSub-Pulmonology Department of Internal Medicine, Faculty of Medicine, Hang Tuah University, Surabaya 57600, Indonesia.

Tiffany Tiara PakasiNational TB Program, Directorate of Communicable Disease Prevention and Control, Ministry of Health Indonesia, Jakarta 10710, Indonesia.

Zakiyathun NuhaTuberculosis Laboratory, Institute of Tropical Disease, Universitas Airlangga, Surabaya 60115, Indonesia.

Manabu AtoDepartment of Mycobacteriology, Leprosy Research Center, National Institute of Infectious Diseases, Tokyo 162-0052, Japan.ORCID 0000-0002-3178-2645

Funding

345/UN3.14/PT/2020 Research Group, Universitas Airlangga

6 · The paper itself

Abstract

Tuberculosis (TB) and COVID-19 have become significant health problems globally, especially in countries with high prevalence. Therefore, this research aims to examine all possibilities and predict the impact of TB-SARS-CoV-2 co-infection to anticipate the cascade effect of both diseases in all sectors. The conceptual strategy of the algorithm in TB-COVID-19 is needed to create an integrated management system. It includes the stages of early detection with accurate and effective methods, as well as the synchronization of TB-COVID-19 health services, starting from primary health facilities to secondary and tertiary referral centers. The algorithm in TB-COVID-19 is crucial to prepare future strategies for PTB co-infection viral respiratory infections other than SARS-CoV-2, ILI, ARI, and SARI. Since the implementation involves all health services, there is a need to integrate the governance of TB-COVID-19 and other comorbidities in good health services based on research and multicentre design.

Indexed as

algorithmCOVID-19integrated managementrespiratory infectiontuberculosis

Identifiers

PMID36355911

DOI10.3390/tropicalmed7110367

PMCPMC9694243

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.