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Record W4287523027 · doi:10.4103/jncd.jncd_69_21

Epidemiological transition and the dual burden of communicable and noncommunicable diseases in Zimbabwe

2021· article· en· W4287523027 on OpenAlexaboutno aff
Prosper Nyabani

Bibliographic record

VenueInternational Journal of Noncommunicable Diseases · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsEpidemiological transitionEpidemiologyContext (archaeology)PopulationSocioeconomic statusNon-communicable diseaseDemographic transitionDeveloping countryGeographyDevelopment economicsEconomic growthPublic healthPolitical scienceMedicineEnvironmental healthEconomicsFertility

Abstract

fetched live from OpenAlex

Background: The epidemiological transition model, coined by Abdel Omran in 1971, building on the demographic transition theory developed by Frank Notestein in 1945, has been largely credited for describing epidemiological situations both globally and nationally in many parts of the world. However, owing to its origins in the United States of America (USA), scholars critique the model's applicability to various geographical, socioeconomic, and epidemiological contexts, which are diversely different from the USA and vary from region to region. It was imperative to test the applicability of this model in sub-Saharan Africa (SSA), particularly Zimbabwe to ascertain versatility in describing epidemiological transitions, predicting population health status and whether the assumption of a shift from communicable diseases (CDs) to noncommunicable diseases (NCDs) could be confirmed in a low-income developing nation focusing on Zimbabwe. Methods: The study was a retrospective document review case study, using the existing framework of the epidemiological transition model, as a guiding principle, applying the model to describe the demographic and epidemiological circumstances prevailing within Zimbabwe. The researcher reviewed, compared, analyzed, and described the existing literature on population dynamics and epidemiological profile of the country for the period 1990–2020. Results: The epidemiological transition model attempts to describe the changes in epidemiological circumstances both at national and global scales. The model presumes a shift in CDs to NCDs. However, many scholars question the applicability of the model to diverse contexts, particularly within the SSA context. The Zimbabwean case was considered in light to its rising population growth, dual burden characterized by a high burden of communicable and rising NCDs. Findings from this study indicate that NCDs are on the rise in Zimbabwe. However, owing to a high burden of CDs, a dual disease burden model is the best fit to explain the epidemiological transition currently obtaining within Zimbabwe. Conclusions: Consequentially, funding streams targeting CDs should take heed of the currently obtaining epidemiological situation in the country and respond by challenging funding to public health interventions with a view to address the rising NCDs. Further, public health authorities should craft Public health policies that create supporting environments conducive for the populace to fight NCDs. Informed by the Ottawa charter, reorientation of health services to ensure more health systems responsiveness in the face of emerging NCDs is imperative. In addition, developing interpersonal skills for individuals to be able to act against NCD's risk behaviors and factors is key; at the same time, strengthening community action by capacitating community health workers to address risk behaviors and factors associated with NCDs at community level is imperative. Finally, the inadequacy of the epidemiological transition model inadvertently challenges epidemiologists to step up efforts to review, refine, and extend the model to suit SSA countries like Zimbabwe and elsewhere countries in similar circumstances.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.399
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.029
GPT teacher head0.317
Teacher spread0.288 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations9
Published2021
Admission routes1
Has abstractyes

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