Impact Factors of Epidemiology and Public Health Journals

Below are 2005 journal IMPACT FACTORS for epidemiology and public health-related journals.

Visit here for general science and general clinical journal impact factors.

Epidemiology & Public Health

American Journal of Epidemiology 5.1
Genetic Epidemiology 5.1
Epidemiologic Reviews 4.7
Cancer Epidemiology Biomarkers and Prevention 4.5
Epidemiology 4.0
International J Epidemiology 4.0
Annual Review Public Health 3.7
Am J Public Health 3.6
Am J Preventive Medicine 3.2
J Epidemiology and Community Health 3.0
J Clinical Epidemiology 2.5
Infection Control Hospital Epidemiology 2.4
Annals of Epidemiology 2.3
Preventive Medicine 2.2
Public Health Nutrition 1.9
Paediatric Perinatal Epidemiology 1.8
Epidemiology and Infection 1.7
BMC Public Health 1.7
Public Health Reports 1.5
European J Epidemiology 1.4

Precipitous Decline of NIH R01 Success Rates

The rate of NIH grant application success has fallen precipitously in the past few years. Although NIH Director Elias Zerhouni's recent Science commentary "touted" that success rates will decline to only 19% next fiscal year, this is affected by the fact that while competitive continuation success rates hover around 32%, actual funding success rate of NEW unsolicited R01 applications was only a meager 9%! See table below. This is a drop from 55% and 20% just 5 years ago.

Seriously, scientists, particularly new investigators cannot possibly be expected to spend time writing 10 different grants just to get 1 funded. There wouldn't be any time to DO REAL SCIENCE anymore, not to mention feed the family!

If the R01 funding mechanism is supposed to be the bread and butter of most independent investigators in the nation, it is easy to imagine a large proportion of scientists with careers stunted and unable to attain promotion, tenure, and forced to leave academia. Also, at the time when graduation rates of math, science, and engineering students is on the decline in the U.S. compared to Japan, China, and Europe-- it is shuddering to think how such an inhospitable environment for science may influence new scientific innovations and discoveries in the U.S. and discourage future generations of students from pursuing science to pursue alternative careers.

Table. Fate of unsoliciated R01 research grant applications, by new and competitive renewal grant applications. (Source: NIH)
(Click to enlarge)

H-index Calculator of Scientist Impact and Influence

The H-index, a.k.a. Hirsch number, created by physicist Jorge Hirsch, is an index is designed to go beyond simple statistics such as the total number of citations or publications, to distinguish influential scientists from those who simply publish many papers. The H-index, which accounts for both is also not highly sensitive to single papers that have many citations. The H-index is relatively effective in comparing researchers working in the same scientific field, and not comparable across disciplines due to different publishing and citation patterns.

The H-index was recently also recognized and featured in an article published in Nature, "Index aims for fair ranking of scientists" Nature. 2005 Aug 18;436:900, which highlighted the H-index's potential use in informing decisions regarding a scientist's tenure, promotion, election to scientific bodies such as the National Academy of Science, and the Royal Society, as well as informative in determining a scientist's impact relative to Nobel Prize laureates.

This Google-based H-INDEX calculation program, developed by Michael Schwartzbach, computes the the H-index number of an individual scientist's scientific impact and influence, based on the original methods described by Hirsch 2005. This web program uses the reputable Google Scholar engine's scientific citation database as basis for calculation.

Name of scientist: (required)



Other optional search parameters:

--Additional key words: (This option is only necessary for non-unique names. One may use AND, OR options in queries. We recommend using academic institution, geographic location, or scientific discipline keywords as optional search terms)


--Scientific discipline: (leave all unchecked to search all fields)

Biology, Life Sciences, and Environmental Science
Medicine, Pharmacology, and Veterinary Science
Engineering, Computer Science, and Mathematics
Physics, Astronomy, and Planetary Science
Chemistry and Materials Science
Business, Administration, Finance, and Economics
Social Sciences, Arts, and Humanities

**Note: This calculation service may experience heavy server load at peak times of the day. Also, because this program directly interfaces with the Google Scholar database, Google may limit the total number of pings by users in a given period of time. Therefore, please be patient if this program is temporarily unavailable, and bookmark this site and return at an off-peak time to run the program. Thank you.***

Impact Factors in Prediction of Future Citations

Although many of us have heard mention of the use of the journal impact factor as an indicator of the impact or quality of scholars' work, little empirical work has been done on this application to date. Does it make sense for academic employment decision makers (e.g. promotion and tenure committees, deans, etc.) to use the impact factor score as an proxy indicator of the eventual impact of a scholar’s work in those instances where that work is so new that the pattern of citations it will attract is unknown?

Holden et al. 2006 explored this question using a random sample of 323 articles selected from 17 social work journals listed in Journal Citation Reports. In this sample from the 1992-1994 period, they found that the impact factor of the journal the article was published in predicted less than 12% of the variance in outcome (r=0.4) at either four or ten years in the future. Given these short and long term results, the authors concluded that the practice of using the impact factor as a proxy indicator of article impact is not supported at this time and further research may be needed.

However, relevance to epidemiology journals is unknown. Furthermore, the modest correlation of current journal impact factor in prediction future citation may be due to temporal trends in the prominence of a journal itself.

Overall, journal impact factors have a list of limitations to overcome.


Holden, G., Rosenberg, G., Barker, K. & Onghena, P. (2006). An assessment of the predictive validity of impact factor scores: Implications for academic employment decisions in social work. Research on Social Work Practice, 16, 6, 613-624.

Major Limitations of Impact Factors of Journals

Publishing articles in journals with impact factors can sometimes make or break a scientist's career, as it often influences decisions regarding promotion, tenure, funding allocation to various university departments and divisions, etc.

However, the use of impact factors for such purposes has often been criticized as there are many potential limitations to journal impact factors. Below we list 20 potential limitations.

Limitations of Journal Impact Factors

• Journal impact factors are not representative of individual journal articles
• Journal impact factors correlate poorly with actual citations of individual articles
• Authors use many criteria other than impact when submitting to journals
• Potentially manipulateable via self citations
• Journals can inflate impact factors by publishing greater proportion of review articles, which are heavily cited
• Long articles collect many citations and give high journal impact factors
• Short publication lag allows many short term journal self citations and gives a high journal impact factor
• Citations in the national language of the journal are preferred by the journal's authors
• journal self citation: articles tend to preferentially cite other articles in the same journal
• Editorial board coerced self citation: editors may suggestively coerce authors to include and cite additional relevant articles from the same journal as criteria for resubmitting manuscript

• Citations to "non-citable" items are erroneously included in the database
• Coverage of the database is not complete
• Books are not included in the ISI database as a source for citations
• Database has an English language bias
• The database of included journals may vary over time, causing instability of impact factor values
• Research fields with literature that have high rates of citation due to the nature of rapidly updated and outdated study results
• Impact factor depends on dynamics (expansion or contraction) of the research field
• Small research fields tend to lack journals with high impact
• Relations between fields (clinical v basic research, for example) strongly determine the journal impact factor

Glossary of Common Epidemiology Terms

Acute disease—a short-term illness, whether mild or fatal. A cold is an acute disease, as is influenza.

Association—when one characteristic is related to another and they change predictably together.

Bias—the amount we are off from the true value. How wrong we are when we don’t get it right.

Biostatistics—the theory and techniques for describing, analyzing, and interpreting health data.

Case—a person in a study who has the particular disease or condition that is being studied.

Cause—a factor or event that produces a second event. In public health, a factor that increases the probability of developing a disease; smoking, for example, causes lung cancer.

Chronic disease—a disease that lasts a long time; often has many causes.

Cohort—a group of people that may share a common characteristic (i.e., they live in a certain town or were born in a certain year) and who are enrolled in a study. The group have their health status followed for a period of time.

Control— a person or group used for comparison. In a trial (experiment), the control group does not receive the drug or agent being tested.

Data—the information collected during a scientific study.

Disease—a term of health status; when something is wrong with a bodily function

Disease cluster—a series of disease cases closely grouped in a specific geographical area or over a specific period of time.

Endemic—the usual existence of an infectious disease in certain areas. For example, malaria is native, or endemic, in southern India because it always infects the mosquitoes of southern India and can be transmitted to people.

Epidemic—any unusual occurrence of disease, generally first noticed by an unexpected number of cases occurring over a particular amount of time or in a particular place. An outbreak of disease, infections or injuries within a defined geographic area or over a specific period of time.

Epidemiology—the use of medical science and statistics to track population health and to find causes of diseases in groups of people.

Exposure—an external factor that may affect health. Cigarette smoking is a well-studied exposure.

Health—a state of complete physical, mental, and social well-being and not just the absence of disease or infirmity.

Incidence—the rate of new cases of disease in a population.

Infectiousness— the relative ease with which an infectious disease is transmitted.

Morbidity—any departure, subjective or objective, from a state of physiological or psychological well-being. Morbidity is generally used to describe non-fatal health events. Sickness.

Mortality—number of deaths or expected deaths in a population; the death rate.

Pandemic—an epidemic occurring over a very wide area, crossing international boundaries and usually affecting large numbers of people. A global disease epidemic.

Population—a group of people defined by some characteristic, such as living in the same place.

Prevalence—the amount of existing disease in a given population at a certain time.

Public health—an effort organized by society to protect, promote, and restore the people’s health. Physicians treat one patient at a time; public health workers treat whole populations.

Risk—the probability that an event will occur (e.g., that an individual will become sick or die) within a stated period of time or at a particular age.

Risk factor—conditions or exposures that can influence the chances that we stay healthy, develop a disease, or die prematurely. Some risk factors are impossible for us to change, like our genes. Other risk factors we can change. The latter are called modifiable risk factors, and include things like our diet, exercise habits, and smoking.

Screening—the use of medical tests or other procedures to identify disease, often at an early stage.

Shift—big changes in the genetics of a virus strain due to mutation. A flu virus may have “shifted” if it is significantly different from strains that have circulated in recent years.

Surveillance—the collection and analysis of timely health information; these data are then used to monitor health and disease in a population.

Transmission—any means of spreading infectious disease to or among people.

(more to be added in the future per request)

AIDS and Creutzfeldt-Jakob Disease data in UK

Website Feature:

www.AIDSCJDUK.info provides comprehensive annual data, reports and forecast projections for HIV/AIDS and variant Creutzfeldt-Jakob Disease (vCJD) in the UK. Based on the data provided by the Health Protection Agency, the website features HIV/AIDS data since December 1999 and vCJD data since March 1994.

Edward G. Collier MBCS CITP
Edwardhfd [at] AOL.COM