Application of Meta-analysis in disease intervention research

In the previous article, various statistical methods and tools were discussed whereby meta-analysis is also an important statistical tool. Meta-analysis is a statistical technique that combines the findings from independent studies, such as clinical studies, epidemiological studies and intervention studies (Uman, 2011). There must be no biases in the study and one must always look for the presence of heterogeneity and explore the robustness of the main finding by calculating the sensitivity. Disease intervention is a technique used to either control, cure, or eradicate health-related issue or disease.

The article discusses the role of Meta-analysis mainly in disease intervention and their importance in epidemiological studies. The intervention method considered in this study are Government policies towards healthcare.


Meta-analysis is mostly used to evaluate the effectiveness of healthcare interventions from the studies of clinical trials of new drugs or medical devices or any other type of intervention. Researchers combine the data collected in the form of particular parameters based on two or more randomized control trials and find their efficacy. Meta-analysis helps to demonstrate the pharmacological properties of the drugs or device, their effects and to establish their efficacy or safety for epidemiological studies (Rohrig et al., 2009).

The meta-analysis uses observational clinical studies where the data collected combine the results from the treatment of the population. The data is then implemented in epidemiological studies. The data comprises of diagnosis, treatment, and monitoring results. Meta-analysis is also utilized by the pharmaceutical companies to take the approval for novel drugs and epidemiological studies. It is also applied in the research of medicine and research to determine the efficiency of various interventions and plan further for epidemiological studies.

Role of Meta-analysis in epidemiology studies

The meta-analysis performed on epidemiological data have their importance in forming efficient government policies. The epidemiological studies are of two types i.e. Interventional studies and Observational studies. The meta-analysis performed on both of these studies have their own role in the disease intervention (Rohrig et al., 2009). Meta-analysis has a major role in government to form policies to prevent the exposure of the disease-causing factor in the affected populations.

The meta-analysis performed on the interventional studies shows us the effect of certain selected factors on the person affected by a disease.

For example, the impact of iodine supplements present in salt on the patients suffering from hypothyroidism. Observational studies, on the other hand, are of two types i.e.Cohort studies and Case-control studies.

A meta-analysis performed on the observational studies is suited to detect connections between exposure of disease-causing elements and development of disease over time. Therefore, the prevalence of the disease in the population due to the particular disease-causing factor can be easily studied. This will eventually help the government to form policies to prevent the exposure of the disease-causing factor in the affected populations.

Types of Epidemiological studies

Types of Epidemiological studies

Meta-analysis in epidemiology help in improving the efficacy of the government policies to eradicate a disease. This also helps in further development of the policies over time by studying the impact of the policy on the affected population for disease intervention. This also helps in the preparation of drugs against the disease and checks their efficiency and effect on the population (Weingarten et al., 2002).

Meta-analysis for disease intervention research

Disease intervention researches are studies that research on finding new methods or improving existing methods to either eradicate or control diseases. Meta-analysis provides a precise estimation of a drug’s efficacy or treatment method. Precise estimation helps in treating and controlling the prevalence of the disease by giving due importance to different studies (Crombie and Davies, 2009).

While researching on a new intervention to control diseases, meta-analysis help in assessing the efficacy of the intervention amongst different populations and their reaction considering various factors. These factors include climatic conditions, geographical locations, genetic build up, and economic conditions (Harvey et. al., 2009). Therefore meta-analysis help in customizing intervention methods according to the factors. This provides a better edge to disease management in a diverse country like India.

Customization of the disease leads to another role of meta-analysis, which is improving the efficacy of an existing drug. Periodical meta-analysis of an existing intervention method helps in assessing the strength of efficacy and linking it to the internal or external factors (Haidich, 2010). In this type of intervention research, meta-analysis helps to assess the validity of an existing treatment method.

Meta-analysis in an intervention research helps to determine the strength of evidence present on a disease and treatment. In other words, meta-analysis determines the efficacy of an effect; and whether the effect is positive or negative and thereby estimate the effect statistically for further intervention research (Haidich, 2010). Therefore meta-analysis in intervention studies helps to determine the precision of estimates of an effect.

Meta-analysis in disease intervention studies

Meta-analysis in disease intervention studies

Disease intervention research for better healthcare

Meta-analysis is now a hallmark of evidence-based medicine. It helps in studying various disease prevalence patterns and effects on various disease management programs. Disease intervention researches, however, play a role in the development of various disease management programs and policies. The researches help determine the efficacy of the treatment plans and disease management and even plan for the efficiency of the treatment plans. Disease intervention studies help determine the overall quality of the evidence of diseases and its existing interventions. Disease intervention research also helps in determining the effectiveness of treatment.

Various countries like USA, UK and Japan use meta-analysis studies for implementation and disease intervention research (Haidich, 2010). Meta-analyses have helped these countries with important insight into the utility of the results to public health care and disease management. The meta-analyses in disease interventions have helped determine validity, magnitude, and applicability for the betterment of health care.

There are other methods that are helpful in assessing the effectiveness of an intervention, such as observational research and statistical studies. However, meta-analysis is a better method for determining the efficacy and validity of the intervention.


  • Crombie, I. K. and Davies, H. T. (2009) ‘What is meta-analysis?’, Evidence Based Medicine, 16(1), pp. 3–4. doi: 10.1136/eb-2012-101118.
  • Haidich, A.B., 2010. Meta-analysis in medical research. Hippokratia14(Suppl 1), p.29.
  • Harvey, S.T., Boer, D., Meyer, L.H. and Evans, I.M., 2009. Updating a meta-analysis of intervention research with challenging behaviour: Treatment validity and standards of practice. Journal of Intellectual and Developmental Disability34(1), pp.67-80.
  • Rohrig, B. et al. (2009) ‘Types of study in medical research: part 3 of a series on evaluation of scientific publications.’, Deutsches Arzteblatt international. Germany, 106(15), pp. 262–268. doi: 10.3238/arztebl.2009.0262.
  • Uman, L. S. (2011) ‘Systematic Reviews and Meta-Analyses’, Journal of the Canadian Academy of Child and Adolescent Psychiatry. Canadian Academy of Child and Adolescent Psychiatry, 20(1), pp. 57–59. Available at:
  • Weingarten, S. R. et al. (2002) ‘Interventions used in disease management programmes for patients with chronic illness—which ones work? Meta-analysis of published reports’, BMJ : British Medical Journal. BMJ, 325(7370), p. 925. Available at:
Diksha Tomer

Diksha Tomer

Research Analyst at Project Guru
She is a bachelor in Botany honours from Miranda House (Delhi University) and is pursuing her master’s in Plant Biotechnology at TERI SAS. She is a recipient of Hemendra Kothari Scholarship and her interests lie in the field of Bioinformatics and Biotechnology.
Diksha Tomer

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