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      Clinical manifestations of Rift Valley fever in humans: Systematic review and meta-analysis

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          Abstract

          Background

          Rift Valley fever (RVF) is an emerging, neglected, mosquito-borne viral zoonosis associated with significant morbidity, mortality and expanding geographical scope. The clinical signs and symptoms in humans are non-specific and case definitions vary. We reviewed and analysed the clinical manifestations of RVF in humans.

          Methods

          In this systematic review and meta-analysis we searched on different dates, the Embase (from 1947 to 13 th October 2019), Medline (1946 to 14 th October 2019), Global Health (1910 to 15 th October 2019), and Web of Science (1970 to 15 th October 2019) databases. Studies published in English, reporting frequency of symptoms in humans, and laboratory confirmed RVF were included. Animal studies, studies among asymptomatic volunteers, and single case reports for which a proportion could not be estimated, were excluded. Quality assessment was done using a modified Hoy and Brooks et al tool, data was extracted, and pooled frequency estimates calculated using random effects meta-analysis.

          Results

          Of the 3765 articles retrieved, less than 1% (32 articles) were included in the systematic review and meta-analysis. Nine RVF clinical syndromes were reported including the general febrile, renal, gastrointestinal, hepatic, haemorrhagic, visual, neurological, cardio-pulmonary, and obstetric syndromes. The most common clinical manifestations included fever (81%; 95% Confidence Interval (CI) 69–91; [26 studies, 1286 patients]), renal failure (41%; 23–59; [4, 327]), nausea (38%; 12–67; [6, 325]), jaundice (26%; 16–36; [15, 393]), haemorrhagic disease (26%; 17–36; [16, 277]), partial blindness (24%; 7–45; [11, 225]), encephalitis (21%; 11–33; [4, 327]), cough (4%; 0–17; [4, 11]), and miscarriage (54%) respectively. Death occurred in 21% (95% CI 14–29; [16 studies, 328 patients]) of cases, most of whom were hospitalised.

          Discussion

          This study delineates the complex symptomatology of human RVF disease into syndromes. This approach is likely to improve case definitions and detection rates, impact outbreak control, increase public awareness about RVF, and subsequently inform ‘one-health’ policies. This study provides a pooled estimate of the proportion of RVF clinical manifestations alongside a narrative description of clinical syndromes. However, most studies reviewed were case series with small sample sizes and enrolled mostly in-patients and out-patients, and captured symptoms either sparsely or using broad category terms.

          Author summary

          Rift Valley fever (RVF) is a neglected, arboviral zoonosis that causes severe and diverse disease manifestations in humans. Currently no licenced vaccines exist for use in humans and there is limited surveillance and estimation of disease burden which in part is due to the inability to concisely define the disease. We searched Medline, Embase, Global Health, and Web of Science for published reports on the clinical manifestations of RVF in humans. Studies published in English, reporting frequency of symptoms in humans, and laboratory confirmed RVF were included. We excluded animal studies, studies among asymptomatic volunteers and single case reports for which a proportion could not be estimated. Pooled symptom frequency estimates were calculated using random effects meta-analysis. This review provides a detailed aggregation of the relative frequency of symptoms, and a description of the RVF clinical manifestations in humans. Previous systematic reviews provided a narrative account and it was difficult to identify the most relevant features of RVF disease in areas where other endemic infections present with similar symptoms. This review will refine the clinical diagnosis, improve case detection, and increase public awareness about RVF presentation in humans.

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          Most cited references108

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          The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials

          Flaws in the design, conduct, analysis, and reporting of randomised trials can cause the effect of an intervention to be underestimated or overestimated. The Cochrane Collaboration’s tool for assessing risk of bias aims to make the process clearer and more accurate
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            Assessing risk of bias in prevalence studies: modification of an existing tool and evidence of interrater agreement.

            In the course of performing systematic reviews on the prevalence of low back and neck pain, we required a tool to assess the risk of study bias. Our objectives were to (1) modify an existing checklist and (2) test the final tool for interrater agreement. The final tool consists of 10 items addressing four domains of bias plus a summary risk of bias assessment. Two researchers tested the interrater agreement of the tool by independently assessing 54 randomly selected studies. Interrater agreement overall and for each individual item was assessed using the proportion of agreement and Kappa statistic. Raters found the tool easy to use, and there was high interrater agreement: overall agreement was 91% and the Kappa statistic was 0.82 (95% confidence interval: 0.76, 0.86). Agreement was almost perfect for the individual items on the tool and moderate for the summary assessment. We have addressed a research gap by modifying and testing a tool to assess risk of study bias. Further research may be useful for assessing the applicability of the tool across different conditions. Copyright © 2012 Elsevier Inc. All rights reserved.
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              Metaprop: a Stata command to perform meta-analysis of binomial data

              Background Meta-analyses have become an essential tool in synthesizing evidence on clinical and epidemiological questions derived from a multitude of similar studies assessing the particular issue. Appropriate and accessible statistical software is needed to produce the summary statistic of interest. Methods Metaprop is a statistical program implemented to perform meta-analyses of proportions in Stata. It builds further on the existing Stata procedure metan which is typically used to pool effects (risk ratios, odds ratios, differences of risks or means) but which is also used to pool proportions. Metaprop implements procedures which are specific to binomial data and allows computation of exact binomial and score test-based confidence intervals. It provides appropriate methods for dealing with proportions close to or at the margins where the normal approximation procedures often break down, by use of the binomial distribution to model the within-study variability or by allowing Freeman-Tukey double arcsine transformation to stabilize the variances. Metaprop was applied on two published meta-analyses: 1) prevalence of HPV-infection in women with a Pap smear showing ASC-US; 2) cure rate after treatment for cervical precancer using cold coagulation. Results The first meta-analysis showed a pooled HPV-prevalence of 43% (95% CI: 38%-48%). In the second meta-analysis, the pooled percentage of cured women was 94% (95% CI: 86%-97%). Conclusion By using metaprop, no studies with 0% or 100% proportions were excluded from the meta-analysis. Furthermore, study specific and pooled confidence intervals always were within admissible values, contrary to the original publication, where metan was used.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: InvestigationRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: Funding acquisitionRole: MethodologyRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Negl Trop Dis
                PLoS Negl Trop Dis
                plos
                PLoS Neglected Tropical Diseases
                Public Library of Science (San Francisco, CA USA )
                1935-2727
                1935-2735
                25 March 2022
                March 2022
                : 16
                : 3
                : e0010233
                Affiliations
                [1 ] Department of Clinical Research, London School of Hygiene and Tropical Medicine, London, United Kingdom
                [2 ] Medical Research Council/Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine Uganda Research Unit, Entebbe, Uganda
                [3 ] Institute for Global Health, University College London, London, United Kingdom
                [4 ] MRC International Statistics & Epidemiology Group, London School of Hygiene and Tropical Medicine, London, United Kingdom
                [5 ] Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, United Kingdom
                [6 ] KEMRI WellcomeTrust Research Programme, Kilifi, Kenya
                University of Pittsburgh School of Medicine, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0001-5771-5515
                https://orcid.org/0000-0002-6271-2033
                https://orcid.org/0000-0002-5949-0097
                https://orcid.org/0000-0003-2818-9549
                Article
                PNTD-D-21-00768
                10.1371/journal.pntd.0010233
                8986116
                35333856
                7a19020c-c26e-4778-b5c1-dacfbcd01228
                © 2022 Anywaine et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 31 May 2021
                : 3 February 2022
                Page count
                Figures: 3, Tables: 3, Pages: 28
                Funding
                Funded by: UK Medical Research Council (MRC)
                Funded by: UK Biotechnology and Biological Sciences Research Council (BBSRC)
                Award ID: 16/107/02
                Funded by: PANDORA-ID-NET Consortium
                Award ID: EDCTP Reg/Grant RIA2016E-1609
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100001275, Oak Foundation;
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100010269, Wellcome Trust;
                Award ID: 203077_Z_16_Z
                Award Recipient :
                This work was conducted at the MRC/UVRI and LSHTM Uganda Research Unit which is jointly funded by the UK Medical Research Council (MRC) and the UK Department for International Development (DFID) under the MRC/DFID Concordant agreement and is also part of the EDCTP2 programme supported by the European Union. This project was funded by the UK Biotechnology and Biological Sciences Research Council (BBSRC) and the Medical Research Council (MRC)/Department of Health, through the UK Vaccines Network which is a Government Funding Stream (Grant no: 16/107/02). SL was supported by the PANDORA-ID-NET Consortium (EDCTP Reg/Grant RIA2016E-1609) funded by the European and Developing Countries Clinical Trials Partnership (EDCTP2) programme under the Horizon 2020, the European Union’s Framework Programme for Research and Innovation. GMW is supported by an Oak foundation fellowship and a Wellcome Trust grant (grant number 203077_Z_16_Z). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and health sciences
                Medical conditions
                Tropical diseases
                Neglected tropical diseases
                Rift Valley fever
                Medicine and health sciences
                Medical conditions
                Infectious diseases
                Viral diseases
                Rift Valley fever
                Medicine and health sciences
                Medical conditions
                Infectious diseases
                Zoonoses
                Rift Valley fever
                Medicine and Health Sciences
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                Statistical Methods
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                Custom metadata
                vor-update-to-uncorrected-proof
                2022-04-06
                All data extraction files are available from the London School of Hygiene and Tropical Medicine (LSHTM) database (DOI: doi.org/10.17037/DATA.00002178).

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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