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Record W4387337474 · doi:10.2196/50985

Economic Burden of Mosquito-Borne Diseases in Low- and Middle-Income Countries: Protocol for a Systematic Review

2023· review· en· W4387337474 on OpenAlexvenueno aff
Nagavalli Chilakam, Varsha Lakshminarayanan, Sushanth Keremutt, Ambigai Rajendran, Girish Thunga, Pooja Gopal Poojari, Muhammed Rashid, Nirmalya Mukherjee, Paramita Bhattacharya, Denny John

Bibliographic record

VenueJMIR Research Protocols · 2023
Typereview
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsnot available
FundersKasturba Medical College, Manipal
KeywordsSystematic reviewScopusGross domestic productMedicineMEDLINEGlobal healthDisease burdenGrey literatureEnvironmental healthBusinessPublic healthEconomic growthPopulationPolitical scienceNursingEconomics

Abstract

fetched live from OpenAlex

BACKGROUND: Globally, among all the vector-borne diseases, mosquito-borne diseases are responsible for a substantial number of cases and deaths and amount to an economic cost of US $12 billion per year. However, there is a dearth of systematic research conducted on the economic burden of mosquito-borne diseases. To address the lack of comprehensive information on this topic, a systematic review will be conducted to synthesize evidence for informing targeted policies and strategies addressing this growing burden and for better financial protection of households. OBJECTIVE: The systematic review aims to review the economic burden of mosquito-borne diseases in low- and middle-income countries (LMICs). The review estimates the total cost, which is the compilation of both the direct costs and indirect costs. Additionally, it reports cost estimates per disease, country, and patient. The review outcome will also discuss the impact of the economic burden in terms of out-of-pocket expenditure, catastrophic health expenditure, impoverishment, and gross domestic product impact due to mosquito-borne diseases in LMICs. METHODS: Systematic searches will be conducted in PubMed (MEDLINE), Ovid Embase, Scopus, the cumulative index of nursing and allied health literacy, and Cochrane CENTRAL. Additionally, websites of the World Bank, World Health Organization, and Asian Development Bank as well as grey literature (eg, Malaria No More and the Ministry of Health websites) will be searched to gather comprehensive information on the topic and identify studies published in the English language. The titles and abstracts will be independently screened by 2 reviewers, followed by a full-text review against the inclusion criteria. Disagreements will be resolved through discussion with a third author. The methodological reporting quality of the studies will be evaluated using the Larg and Moss checklist, Cochrane risk-of-bias tool for randomized trials, and the Consensus on Health Economic Criteria. Data will be extracted using a standardized data extraction form. RESULTS: The protocol was registered in PROSPERO (CRD42023427111) prior to the initiation of the search strategy. The review is currently ongoing and will synthesize information from the identified studies through a process involving structured screening, data extraction, and critical appraisal in the form of tables and a narrative summary of studies reporting the economic burden incurred due to mosquito-borne diseases in LMICs. CONCLUSIONS: This review seeks to report the economic burden of mosquito-borne diseases. It will act as evidence for policymakers to prioritize their decisions regarding containing the prevalence of mosquito-borne diseases and the means to lowering the incidence of diseases spread by mosquitoes. TRIAL REGISTRATION: PROSPERO CRD42023427111; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=427111. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/50985.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.327
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.232
GPT teacher head0.568
Teacher spread0.336 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations41
Published2023
Admission routes1
Has abstractyes

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