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EPIDEMIOLOGY – INTRODUCTORY NUMERICAL CONCEPTS DR LYNNE LAWRANCE.

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Presentation on theme: "EPIDEMIOLOGY – INTRODUCTORY NUMERICAL CONCEPTS DR LYNNE LAWRANCE."— Presentation transcript:

1 EPIDEMIOLOGY – INTRODUCTORY NUMERICAL CONCEPTS DR LYNNE LAWRANCE

2 SESSION AIMS  To build on the introduction to epidemiology that you have covered in SBoD or by catch-up material  To introduce some of the key measures of epidemiological analysis  To actively undertake some epidemiological exercises

3 EPIDEMIC  An epidemic is an unusual or increased adverse effect on the health of the population (though some advocate that it could be used to refer to longer, slower rises in the incidence of some diseases)  Historically it really referred to sudden increases in disease numbers or a rapid geographical spread  Now has been extended to include the more insidious onset illnesses and also health related factors such as “smoking epidemic” or “obesity epidemic”

4 PANDEMIC  A pandemic literally refers to an epidemic that is worldwide in spread  However in common parlance it refers to disease with a cross national boundary or continental boundary  In WHO terms the definition is cases WITH transmission arise in more than one WHO region  We saw this used with the SARS “pandemic”

5 SARS – A “NEW” TYPE OF PANDEMIC  Historic pandemics spread across the land from country to country – a wave like pattern  As trade routes develop the role of boats emerges  Carriage by the military is an issue  Modern pandemics spread in a more random way primarily due to the ease of international travel - aeroplanes

6 CHOLERA V SARS  Second Cholera Pandemic (1820s/30s)  India  Neighbouring countries and those with strong trade ties – e.g. Persia  From Persia to Russia and then from Russia to Poland  Spreads through parts of mainland Europe, including Paris  To Britain by boat from Hamburg  Irish immigrants carry the disease to Quebec  Spread through the Americas  India to Canada takes 6 years  SARS ( 2002)  China  Spread to local countries – particularly Hong Kong  Hotel Metropole in HK is a “superseeding” event with travellers from a number of countries affected who then return home by plane  Canada outbreak identified  More spread in SE Asia  Sporadic cases in many countries including US, UK, France, Germany BUT all cases are imported  China to Canada takes ~6 months (though not easy to be precise): Hong Kong to Canada took ~ 1 week!!

7 ENDEMIC  An endemic disease is one that “native to” a population or “belonging to the people”  The illness occurs at a roughly even level of illness within the population  Here principles of epidemiology can be used to try and understand how and why a disease arises in the population it has become native within

8 MORTALITY  Death!!!  Generally measured in terms of case fatality rate or the mortality rate  The “crude” mortality rate is the number of people in a population who die of a given disease per specified unit of time  Case-fatality rate – the number of deaths from a disease in a specified time per number of diagnosed cases of the disease  Both often require refining to gender/age etc as risk of death varies with sub-groups

9 MORBIDITY  Additionally covers non-fatal aspects of a disease, such as disability or general feeling of “being ill”  Morbidity is difficult to quantify, but figures such as hospital admission rates, working days lost etc attempt to address this area  The term morbidity is not used consistently in publications or even epidemiological texts

10 OTHER TERMS YOU MAY ENCOUNTER  Infant mortality rate – number of infant deaths (<1year) per number of live births  Fertility rate – the number of live births per number of women aged 15-44yrs  Case fatality rate – of the people who have the disease how many people die FROM it?

11 PREVALENCE  The prevalence of a disease is the “proportion of a population that are case at a point in time”  Prevalence is most suitable when considering relatively stable conditions it is generally not used for acute illnesses  Consequently prevalence is rarely used for bacterial diseases in the developed world. It could however be used with reference to chronic infections (e.g. HIV), or to endemic infections in the developing world.  Prevalence would work well for diseases such as diabetes, congestive heart disease, cystic fibrosis

12 FACTORS THAT INFLUENCE PREVALENCE RATE  Disease severity - in severe infections people may die rapidly - this will reduce the prevalence  Duration of the illness – if a disease lasts a short time its prevalence is lower than if the disease lasts a long time  The number of new cases (i.e. the incidence) – if many people acquire a disease its prevalence generally also rises  Medical intervention – in some incurable diseases patients life’s can be prolonged  Improved diagnosis – the development of a more sensitive test may result in an increase in prevalence  Migration – the influx of migrant with an illness can increase prevalence as could the efflux of healthy people, however the converse can also be true  Improved cure rates will decrease the prevalence

13 INCIDENCE  The incidence of a disease is “the rate at which new cases occur in a population in a specified period”  There are a number of different formulae for incidence dependent on precisely what you want to examine  For many infectious diseases this is based on the “notification rate” rather than the actual number of cases  For other diseases incidence may be determined during screening programmes, through specific calls for data from health care providers, the studies described earlier

14 RELATIVE RISK  Relative risk is the ratio of the disease rate in a “risk exposed” population compared to the disease rate in a non- exposed population  Where more than one risk factor is involved, their relative risks often multiply each other (more relevant to multi-factorial diseases such as cancer)

15 INTERPRETING RISK  Clearly high relative risk or other value may give strong evidence as to the cause of a disease o source of an infection  However – even a low relative risk could be important if large numbers of people are exposed, or if people undergo multiple exposure events


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