A preregistered meta-meta-analysis on the global distribution of Hepatotropic Viruses

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Introduction. Hepatotropic viruses (HAV, HBV, HCV, HDV, and HEV) significantly impact global health, with varying prevalence across regions.

Objective. This study aims to systematically consolidate data from diverse meta-analyses to provide a contemporary reference on virus distribution and prevalence.

Materials and methods. Adhering to PRISMA guidelines, the study utilized a mixed effects model for data integration. Quality evaluation was carried out with QUOROM and AMSTAR tools, with heterogeneity assessed via the Higgins I2 statistic, Q-statistic and Tau squared (τ2) values.

Results. The study analyzed 86 meta-analyses from 56 studies (2017–2022) with minimal overlap. Prevalence rates by region were as follows: MENA – 29.2%, Afghanistan – 9.14%, Africa – 8.10%. Prevalence rates by virus type: HAV – 82.5%, HBV – 8.6%, HCV – 15.1%, HDV – 8.9%, HEV – 13.9%, dual HBV-HCV coinfection – 2.2%. Prevalence rates by risk groups: general population – 8.3%, healthcare workers – 4.0%. Continent-specific HBV-HCV prevalence rates: Africa – 9.2%, China – 6.9%, others. HCVprevalence rates among at-risk groups: healthcare workers – 5.58%, hemodialysis patients – 34.8%. Regional HCV rates: Africa – 7.42%, Middle East – 25.30%.

Conclusion. Diverse global hepatotropic virus prevalence patterns are influenced by multifaceted factors. MENA faces higher rates due to healthcare challenges, while Africa struggles with limited resources. Tailored public health strategies, including vaccination and awareness campaigns, are essential to alleviate burdens and enhance global health. This consolidated data serves as a valuable resource for informed decision-making.

作者简介

Shuaibu Suleiman Adeiza

Ahmadu Bello University; Usmanu Dafodiyo University

编辑信件的主要联系方式.
Email: suleykestler2@gmail.com
ORCID iD: 0000-0002-9293-2600

PhD, Head of Clinical Practice Laboratory, Department of Pharmaceutical Microbiology & Biotechnology, Faculty of Pharmaceutical Sciences, Department of Clinical Pharmacy and Pharmacy Practice, Faculty of Pharmaceutical Sciences

尼日利亚, Zaria; Sokoto

Md. Aminul Islam

President Abdul Hamid Medical College; Noakhali Science and Technology University

Email: aminul@pahmc.edu.bd
ORCID iD: 0000-0003-1091-9726

MSc, PhD Scholar of Cell and Molecular Biology, Advanced Molecular Lab, Department of Microbiology, President, COVID-19 Diagnostic Lab, Department of Microbiology

孟加拉国, Karimganj, Kishoreganj, 2310; Noakhali, 3814

Hauwa’u Umar Mungadi

Usmanu DanFodiyo University

Email: hauwaumarmng@gmail.com
ORCID iD: 0000-0001-7200-1035

PhD, Head of Department, Department of Veterinary Medicine, Faculty of Veterinary Medicine

尼日利亚, Sokoto

Abdulmalik Bello Shuaibu

Usmanu DanFodiyo University

Email: abdulmalik.shuaibu@udusok.edu.ng
ORCID iD: 0000-0001-7684-2472

PhD (student), Head of Laboratory Virology Unit, Department of Veterinary Microbiology, Faculty of Veterinary Medicine

尼日利亚, Sokoto

Ranjit Sah

Institute of Medicine; Dr. D. Y. Patil Medical College, Hospital and Research Centre, Dr. D.Y. Patil Vidyapeeth

Email: ranjitsah@iom.edu.np
ORCID iD: 0000-0002-2695-8714

PhD, Head of Influenza and COVID-19 Testing (National Influenza Center), Department of Microbiology, Tribhuvan University Teaching Hospital, Department of Microbiology

尼泊尔, Kathmandu 44600; Pune, 411018, Maharashtra, India

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2. Fig. 1. PRISMA flow chart of included meta-analysis.

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3. Fig. 2. A forest plot of Distribution and prevalence of hepatotropic viruses across diverse geographical regions (a) and assessment of Heterogeneity in Prevalence Rates (b).

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4. Fig. 3. Forest plot of: Subgroup analysis by Virus types (a); Composite prevalence rates of HBV infection among different risk groups (b); Prevalence of HBV varied across different continents (c); Prevalence of HCV among populations at risk (d); Regional prevalence of HCV (e).

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Согласие на обработку персональных данных с помощью сервиса «Яндекс.Метрика»

1. Я (далее – «Пользователь» или «Субъект персональных данных»), осуществляя использование сайта https://journals.rcsi.science/ (далее – «Сайт»), подтверждая свою полную дееспособность даю согласие на обработку персональных данных с использованием средств автоматизации Оператору - федеральному государственному бюджетному учреждению «Российский центр научной информации» (РЦНИ), далее – «Оператор», расположенному по адресу: 119991, г. Москва, Ленинский просп., д.32А, со следующими условиями.

2. Категории обрабатываемых данных: файлы «cookies» (куки-файлы). Файлы «cookie» – это небольшой текстовый файл, который веб-сервер может хранить в браузере Пользователя. Данные файлы веб-сервер загружает на устройство Пользователя при посещении им Сайта. При каждом следующем посещении Пользователем Сайта «cookie» файлы отправляются на Сайт Оператора. Данные файлы позволяют Сайту распознавать устройство Пользователя. Содержимое такого файла может как относиться, так и не относиться к персональным данным, в зависимости от того, содержит ли такой файл персональные данные или содержит обезличенные технические данные.

3. Цель обработки персональных данных: анализ пользовательской активности с помощью сервиса «Яндекс.Метрика».

4. Категории субъектов персональных данных: все Пользователи Сайта, которые дали согласие на обработку файлов «cookie».

5. Способы обработки: сбор, запись, систематизация, накопление, хранение, уточнение (обновление, изменение), извлечение, использование, передача (доступ, предоставление), блокирование, удаление, уничтожение персональных данных.

6. Срок обработки и хранения: до получения от Субъекта персональных данных требования о прекращении обработки/отзыва согласия.

7. Способ отзыва: заявление об отзыве в письменном виде путём его направления на адрес электронной почты Оператора: info@rcsi.science или путем письменного обращения по юридическому адресу: 119991, г. Москва, Ленинский просп., д.32А

8. Субъект персональных данных вправе запретить своему оборудованию прием этих данных или ограничить прием этих данных. При отказе от получения таких данных или при ограничении приема данных некоторые функции Сайта могут работать некорректно. Субъект персональных данных обязуется сам настроить свое оборудование таким способом, чтобы оно обеспечивало адекватный его желаниям режим работы и уровень защиты данных файлов «cookie», Оператор не предоставляет технологических и правовых консультаций на темы подобного характера.

9. Порядок уничтожения персональных данных при достижении цели их обработки или при наступлении иных законных оснований определяется Оператором в соответствии с законодательством Российской Федерации.

10. Я согласен/согласна квалифицировать в качестве своей простой электронной подписи под настоящим Согласием и под Политикой обработки персональных данных выполнение мною следующего действия на сайте: https://journals.rcsi.science/ нажатие мною на интерфейсе с текстом: «Сайт использует сервис «Яндекс.Метрика» (который использует файлы «cookie») на элемент с текстом «Принять и продолжить».