lezione 2 epidemiologia.pptx

Salute/Salute Pubblica
La salute è uno stato di completo benessere fisico, mentale e sociale e non
semplicemente l’assenza di malattia o infermità (OMS 2005b).
La salute può anche essere definita come la capacità di un individuo di adattarsi e
gestire sfide fisiche, mentali e sociali per tutta la vita.
La sanità pubblica è la scienza e l’arte di prevenire le malattie, prolungare la vita e...
promuovere la salute attraverso gli sforzi organizzati e le scelte informate della
società; organizzazioni, pubbliche e private; comunità; e individui (Winslow 1920)

Epidemiologia veterinaria
 L’epidemiologia è lo studio delle malattie nelle
popolazioni e dei fattori che ne determinano il
verificarsi;
 comprende indagini e valutazioni di indicatori
legati alla salute, in particolare alla produttività.
Tutte queste indagini implicano l'osservazione
popolazioni animali e fare comparazioni tra
esseosservazioni.

epidemiologia
 cercare indicatori di malattia basati sulla
popolazione/mandria/gregge mediante
l’osservazione, il confronto e, in alcuni casi, la
sperimentazione.
 due approcci epidemiologici:
 (a) qualitativo (epidemiologia ambientale,
sierologica e molecolare)

epidemiologia
 lo studio della frequenza, della distribuzione e
dei determinanti della malattia in una
popolazione,
 l’obiettivo primario: sviluppare un’adeguata
prevenzione e misure di controllo della
patologia;
 fornire una base scientifica per la pianificazione
di programmi sanitari public health/animal

Health:Dinamica
 La complessa dinamica della relazione tra
ospite, agente patogeno e ambiente implicate
nell’equilibrio instabile e delicato della salute;
 tutte le aree sanitarie veterinaria/medica sono
fondamentali per l’epidemiologia

Relazioni
(1) l'infettività e la patogenicità dell'organismo
causativo;
(2) suscettibilità, resistenza e/o immunità dell'ospite;
(3) il fisico,fattori biologici e socio-economici
dell’ambiente.

Epidemiologia
Pertanto, l’epidemiologia è un approccio scientifico ordinato allo
studio delle condizioni/situazioni e malattie che influiscono sulla
salute e sul benessere dell'uomo e dell’animale.
comprende non solo la popolazione malata ma anche la
popolazione a rischio.

epidemiologia
 L'epidemiologia è uno studio (logos=scienza) su
(=epi) una popolazione (=demos).
 Il termine epizootiologia è più inclusivo (studio
su una popolazione di animali, incluso l’Homo
sapiens).

Triade epidemiologica
 Indaga la connessione tra le popolazioni di
agenti infettivi o di altri fattori causali, la
popolazione ospite e il loro ambiente,
 triade epidemiologica di un sistema
multifattoriale per aver provocato epidemie

Lo studio della storia naturale delle malattie in
una nazione può
essere utilizzato come indice per valutarne la
progressione.
“il progresso umano, ad esempio l’eradicazione
globale del vaiolo”.

una disciplina aperta che deriva
informazioni provenienti da una varietà di
discipline consolidate, come microbiologia,
biotecnologia, statistica-biostatistica,
ambiente, selvicoltura, fauna selvatica ed
ecologia, economia, scienze sociali-
antropologia, ecc. Un epidemiologo è il
capitano e possiede
sesto o senso del cavallo.

epidemiologia
raccoglie dati, tabula per trarre conclusioni
che consentono di formulare ipotesi, rivisitare i
dati se necessario e rivedere i piani.

Epidemiology

 basic and essential to the implementation of the
One Health concept

Based on the Fundamentals/Basics
 General epidemiology; process involving the
agent; the hosts—reservoir and the
susceptibles; the transmission process and the
environment—social, ethnological, ecological,
etc.; and temporal factors.
 Landscape epidemiology; to analyse both risk
patterns and environmental risk factors.
 Descriptive epidemiology; o describe the

Based on the Fundamentals/Basics
 General ; process involving the agent; the
hosts—reservoir and the susceptibles; the
transmission process and the environment—
social, ethnological, ecological, etc.; and
temporal factors.
 Landscape ; to analyse both risk patterns and
environmental risk factors.
 Descriptive; o describe the variations in disease

Based on Diagnostic Methods and the Diagnosis
of Infection/ Disease
 Clinical;
 Sub-clinical;
 Serological;
 Molecular;

Based on Attributes in the Study
Population
 Occupational;
 Disaster;
 Genetic;
 Nutritional;

Based on Application
1. Applied: problems in public health and health service research;
2. Special: it is the theory of the development, control, and prophylaxis of special epidemic or
epizootic diseases, e.g. acquired immunodeficiency syndrome and bovine spongiform encephalitis;
3. Practical:in collaboration with many specialists; applied epidemiology with a multidisciplinary
approach.
4.Theoretical: models are designed to simulate epidemics so as to examine the factors
associated with or responsible for the occurrence of epidemics and work out a strategy to control
ongoing epidemics as well as prevent their occurrence in future.
5.Predictive:the occurrence and trends of a disease
6.Participatory:: it is the application of participatory methods to epidemiological research and
disease surveillance, which overcomes the limitations of conventional epidemiological methods.
7.Computational:it involves the application of computer science to
epidemiological studies

Ecology/Epidemiology
 ‘oikos’=home
 relationships between organisms and their
 environment.

components of the environment
 biotic (living organisms); animals, plants,
microbes, and all other living organisms;
 abiotic or physical forces, including the wind,
sunlight, and soil, as well as man-made
infrastructure;
 Biotic and abiotic conditions may affect the
potential for persistence and/or the
dissemination of contaminants (whether

Environment
 The ecological environment may be considered
as the sum total of all the external influences
and conditions that affect the life process.
 During the process of competition in response
to stimuli of the environment, an organism may
develop a particular morphological form, a
physiological response, or a behavioural
pattern. Such a response is considered an

Biotic community
‘Biotope’: An ecosystem, which provides uniform conditions
of life;
‘Biocoenosis’: the biotic community sharing the ‘biotope’ .
‘Niche’ of an organism in the biotope is its special position;
‘Biome’ is a well-differentiated and climatically uniform
geographical region, such as tundra, grassland, savannah,
tropical forest, and desert.
The biotic community in any ecosystem is the result of the interaction of
all living agents affecting the biotic communities and the soil, water, air,
physical forces, chemical forces, plants, and animals—all interacting with
each other and affecting other’s behaviour

New niches
 The emergence and re-emergence of infectious
agents, including zoonoses, can be considered
a logical consequence of their ecology and
evolution as microbes exploit new niches and
adapt to new hosts.
 Human activities like land use, the extraction of
natural resources, animal production systems
and the use of antimicrobials, global trade, etc.

zoonosi
 ecological niche for the arthropod vectors is
shaped by environmental and anthropogenic
determinants.
 The reservoir, insect vectors, and pathogens
constitute the components of a biocenosis. The
reservoir becomes the donor of infection, with
the insect vector a recipient, which in turn

The study of the natural history of
disease
 requires knowledge of
 (a) the surrounding outer world,
 (b) the organic and inorganic conditions of
existence,
 (c) the so-called economy of nature,
 (d) the correlation between all organisms living
together in one and the same locality,

Health
 Health, opposite to disease, has been defined,
for human beings, as ‘a state of physical,
mental and social wellbeing and not merely the
absence of disease or infirmity’;
 ‘animal health is a state of physical,
physiological and behavioural wellbeing of
animals, which lead to maximum possible levels
of production, draught efficiency and economic

‘dis-harmony or dis-ease’
. Health is considered to be the result of a
harmonious relationship
of an individual with the environment.
Any disturbance in this state of
harmonious relationship that brings at this state.

Koch postulates
 to be accepted as a cause of disease, must
 (a) be isolated in pure culture from a diseased
case and grown in artificial culture media,
 (b) be found in all cases and regularly,
 (c) reproduce the disease in experimental
animals, and
 (d) be re-isolated from the experimental animal

KOCH postulates
 continued to be the guideline for many years
 some diseases could not be adequately
explained!!!!

‘Multifactorial causation of disease’
 The theory brought forward evidence of an
association of factors,other than the specific
infectious agent, in disease causation,

Evans’ postulates
 the ‘causal association of a factor with disease’.
 (a) the incidence and prevalence of disease
must be more in the exposed than in the control
cohorts,
 (b) the cause is more common in the diseased,
 (c) exposure to the agent precedes the
appearance of disease,
 (d) the elimination of the agent results in a

Susser’s criteria
are worth considering when establishing causal association (Susser 1977). These are the
following:
(a) strength—a stronger statistical association denotes a greater possibility for one variable
to positively affect the other;
(b) consistency—the causal association is established on the basis of repeated tests, and
the results are reproducible;
(c) coherence—the association appears reasonable in biological terms;
(d) specificity—the suspected characteristic relates favourably to the precision with which
the occurrence of one variable predicts the other variable;
(e) time order and logical structure—historically, the exposure to disease precedes its
actual occurrence; and
(f) dose-response—the intensity of disease occurrence is related to the dose of the causal
agent

Factors that contribute to disease
causation
 Predisposing factors create a state of
susceptibility, making the host vulnerable to the
agent, e.g. genetics, age, sex, previous illness,
etc.
 Enabling factors are those that assist in the
development of the disease, e.g. poor nutrition,
unhygienic housing, poor sanitation, inadequate
medical care, etc.

Multiple causalities of disease
is the theory that considers holistically the
contribution of each of the three major factors—
‘environment’, ‘host’, and ‘agent’—to the
causation of the disease. A balanced state of the
interaction of ‘host-environment-agent’ results in
‘health’, and any alteration or imbalance leads to
disease

The balanced state
of the host is dependent upon age, sex,
race, habits, customs, genetic factors,
defence system, etc.;
of the agent is determined by the nature
and characteristics of the agent in
relation to the host and the environment;
of the environment is the aggregate of
all external conditions and influences
affecting the agent (non-infectious) or
the life of the agent, host, intermediate
hosts, and vectors;
behaviour/management; or animal
husbandry practices

Agent, Host, and Environmental
Factors

The agent
 Diseases may be caused by the impact of a fall
or accident, emotional breakdown, burn, excess
or lack of certain chemicals, or microscopic and
sub-microscopic agents, as explained below.
 The agent causing disease may be physical,
chemical, biological, or a variety of other factors
whose presence or absence in the host’s
environment leads to ill health, i.e. disease

Agents
 • Physical agents: such as heat, electricity,
radiation, fall, beating, drowning, etc.
 • Chemical agents: such as toxic plants and
feed, agrochemicals, chlorinated naphthalene
used as additives in farm lubricants (causes
bovine hyperkeratosis), and insecticides used
for spray or dips; excess of certain chemicals
(e.g. fluorine) and deficiency of other chemicals

Microorganism identification
 (a) properties useful for identification;
 (b) properties useful for understanding the
agent’s interaction with the host’s tissues and
cells, even at the molecular level;
 (c) host-related properties that explain the
further spread of infection;

Properties useful for identification
These are the taxonomic and antigenic characteristics of a
microorganism. The conventional laboratory tests in isolation and the
characterisation of a microorganism are useful for identification on the
basis of taxonomy, e.g. Gram’s staining, morphology, certain differential
biochemical tests, tissue culture and specific cytopathy, and antigens, like
somatic, flagellar, etc., for serological tests. Specific antigens may be used
to identify the exposure group in the population. A significant increase in
the levels of a specific antibody indicates definite exposure (i.e. it is
diagnostic).The agent’s ability to survive in the environment outside the
host is important for the transmission of infection.

Properties useful for understanding the agent’s
interaction with the host’s tissues and cells, even
at the molecular level
 Various….useful in invasion and initiating
pathological changes in the hosts;
 Lipopolysaccharides (LPSs);
 Means to evade phagocytosis;
 Bacterial adhesins, fimbria and flagella, or viral
haemagglutinin;
 Exotoxins of specific activities, such as the

Host-related properties that explain
the further spread of infection
Infectivity;
Pathogenicity;
Virulence;

Host
 breed, race, ethnic group, occupation or uses,
age, sex, husbandry practices, management
conditons/socio-economic status, physiological
state, previous and concurrent infection/disease
history, herd immunity, behaviour and
resistance, reservoirs, and host specificity of
infection:
 • Heredity: umbilical hernia in calves and

Host
 • Sex: abortion and mastitis are diseases of
females, whereas fistulous wither is more
common in males.
 • Occupation or use: fracture of the long bone in
race horses, fistulous wither in bullocks, mastitis
in milch animals.
 • Nutrition: a well-nourished animal is generally
less susceptible to diseases. Exceptions are

Environment
 is a general term but very inclusive.
 Important components are : climate and
weather, husbandry, open and closed
population, management, housing,
trans_x005F_x0002_port, etc.
 The climate and weather affect the agent, host,
vector, and intermediate hosts and thus

Environment-effect on the host
 fluctuating environmental temperature and
humidity predispose pigs to pneumonia and
calves to mortality;
 The onset of rains is associated with outbreaks
of haemorrhagic septicaemia.
 Winter and frost lower the resistance in sheep
so that they may suffer from braxy. Pendulous
crops in turkey of Bronze breed found in the

Environment-Effect on the agent
 climatic conditions affect the survival of the
agent in the environment. Bacillus anthracis
forms spores very slowly at temperature 21 °C
or below. The vegetative forms are fragile and
are destroyed easily in nature. Therefore,
serious outbreaks of anthrax do not occur in
places where atmospheric temperature is
maintained below 21 °C. Plasmodium can
multiply in mosquitoes’ body at a temperature

Environment-Effect on vectors
Insect vectors like mosquitoes, blow flies, and mites are more active
during warm months.
Environmental temperature affects the infected host and also
influences vector transmission. Mosquitoes feeding upon yellow fever
cases in humans can transmit to susceptibles and can produce
disease in 4 days and 18 days at temperatures of 37 °C and 21 °C,
respectively.

Envinronment-Effect on intermediate
hosts
 snails are active during rains and near pools of
water. The development of the intermediate
stages of liver fluke and amphistomes is
dependent upon the snails’ physiology. During
drought or in summer, snails stop feeding and
become quiescent, and the development of
immature flukes in snails also ceases. Cercaria
will not be laid on the blades of grasses for
infecting cattle. (schistosomiasi)

Environment-Effect on disease
distribution
 the effect on the distribution of diseases could
be indirect through the effect on the host, agent,
vector, and intermediate hosts. Besides, there
may be a direct effect, too. The geo-climatic
conditions determine the type of vegetation.
The distribution of plant toxicities is, thus,
dependent on the environ_x005F_x0002_ment.
Goitre and fluorosis are other examples. The
landscape epidemiology defines natural nidii of

Husbandry Practices
 Open population;
 Closed population;
 Social distance;
 Free-range system;
 Feed;
 Transport;

Time
 Time is also a determinant of disease
occurrence. An example is Monday morning or
after a holiday (post-holiday sickness). Horses
suffer from azoturia, particularly on Mondays.
Overwork on weekend, followed by rest on
Sunday, leads to azoturia or myoglobinuria on
Monday morning. Photoperiodism may
determine the biting time of a vector; e.g., Culex
tarsalis feeds at sunset when birds roost,

Diseases transmission
 Disease is a departure from health and a
manifestation of a morbid condition;
 infectious/non infectious;

Infection Process
 ‘portals of entry’;
 ‘incubation period’ (stage 1);
 ‘symptoms of the disease’ (stage 2):
 - the prodromal phase (stage A);
 - classical symptoms, when the disease is at its peak form, or
fastigium/most intense phase (stage B);
 - the phase of decline or defervescence (stage C)
 cessation of clinical symptoms (stage 3);

Latent and Patent Infection
 LATENT: inapparent infection having the
potential to show/develop signs and symptoms
of the disease.
 In an inapparent infection, the host carries an
infection without disease and the host-parasite
relationship may be commensal.
 PATENCY:Once the infective agent becomes
detectable in the host;

Carriers
animals that harbour an infecting/disease agent,
but displays no symptoms i.e inapparent infection.

Reservoir
 It is one in which the infectious agent naturally
lives and multiples.
 anthroponotic;
 Zoonoses;
 Saprozoonoses;


Source
 man, animal, object, or substance from which
the infectious agent passes to a host. A
contaminated feed/food, contaminated water
supply, or infected man, animal, or insect could
be a source of infection;

Modes of Transmission
 1. Contact
 (a) Direct
 (b) Indirect
 2. Air
 3. Vehicle (non-living object);
 4. Vector

Biological transmission
When the infectious agent of disease undergoes multiplication or some
develop_x005F_x0002_mental changes with or without multiplication;
(a) propagative transmission:the infective agent undergoes multiplication only without any
developmental changes, e.g. Clostridium perfringens type A in meat gravy and plague
bacilli in rats;
(b) cyclo-propagative transmission: the infective agent undergoes cyclical changes as
well as multiplication, e.g. malarial parasites in anopheles mosquitoes;
(c) cyclo-developmental transmission, where the infective agent undergoes cyclical (i.e.
metamorphic) changes only without multiplication in the vector, e.g. filarial parasites in
Culex mosquitoes and guinea worm in cyclops.
(d) development-propagative: that does both, increasing the
num_x005F_x0002_ber as well as changing the stage of the parasite
(example: a single miracidium stage of the liver fluke Fasciola hepatica
enters a Lymnaea snail vector)

The extent of transmission of infectious agents is
dependent upon a number of
factors:
 1. The range of movement of the reservoir,
vector, or vehicle
 2. Survival of the agent outside of the host
 3. The ability of the agent to multiply and
increase in number in the vertebrate and
 invertebrate hosts and in inanimate objects

Disease Distribution in Population
 The occurrence of cases in an uneven and scattered manner in
time and space
 Sporadic;
 The number of cases clearly in excess of the expected number.
If the extent of spatial distribution is :
 very small (local, such as students’ hostel or a farm), called an
outbreak: Outbreak;
 large (district, state, country): Epidemic;
 very large (a number of countries):Pandemic;

Disease Distribution in Population
 Endemic:Diseases indigenous to an area are
called endemic or enzootic. The number of
cases is maintained with less amount of
variation.
 Emerging Diseases:some uncommon, unusual
disease reveal that the disease was either
exotic (not reported earlier in the place/country
of investigation) or emerging (a new disease or

Diseases Distribution in Population
 Cyclic Epidemic Curve
 The epidemic is observed every year (Fig. 8.4).
As in the case of measles, most cases appear
during spring (March–April) every year. A
regular, predictable cyclic fluctuation in
incidence is called ‘endemic pulsation’. The
possible reasons for the season-related cyclic
trend are (a) host density, (b) management

Diseases Distribution in Population
 Secular Epidemic: The new variant emerged
during the time that elapsed between the two
epidemics. Students may refer to the antigenic
shift and antigenic drift observed in the
influenza virus leading to changes in the
haemagglutinin and neuraminidase antigens.

Data in Epidemiology
 qualitative
 describe the
property/characteris_x005F_x0002_tic of
animal, i.e. membership of a group or class, like
the breed, sex, and colours of an animal. The
aggregates of qualitative data are countable,
e.g. the total number of female cows or Red
Sindhi cows or black goats. Qualitative data

Qualitative nominal data
 Nominal: since categories are nominated
names, they are therefore called ‘nominal’. A
nominal scale is also called classificatory scale,
in which the categories cannot be arranged in a
logical order. Each category is considered equal
to the other. Examples are gender
(male/female), blood groups (A/B/O/AB),
religion
(Hindu/Muslim/Christian/Buddhist/Punjabi), and

Qualitative ordinal data
 Ordinal:here, different categories can be
logically arranged in a meaningful order, but the
difference between the categories is not
‘meaning_x005F_x0002_ful’;
 Ranks;
 Likert scale;
 Visual analogue scale (VAS);

Ranks
 can be arranged in either an ascending or a
descending order, but the difference between
ranks will not be the same;
 ‘Best’ is not necessarily twice as good as
‘better’ or four times as good as ‘good’

Likert scale
 the ordering is flexible, for example ‘strongly
agree/ agree/neutral/disagree/strongly
disagree’, and the order can be easily reversed,
viz. ‘strongly
disagree/disagree/neutral/agree/strongly agree’,
without affecting the interpretation, but the
difference between categories is not uniform.
 In the ordinal scale, any transformation must

VAS
 it uses a straight line of 10 cm, divided into 100
equal divisions, the extreme limits like in the
case of the examination of the soundness of a
horse.

Quantitative data
 these relate to amounts, e.g. prevalence,
incidence, body weight, milk yield, antibody
titre, etc.
 These data may be discrete and continuous.
 (a) Discrete data generate counts and have a
specified set of values, such as whole numbers
(1, 2, 7, 9, etc.), e.g. number of teats on a sow,
egg production, etc.

Continuous data:Interval scale
 the values have a meaningful difference and
can be ordered, but doubling is not meaningful
because of the absence of an ‘absolute zero’.
For example, in the Celsius scale, the
difference between 60 and 50 °C is the same as
that between 20 and 10 °C (meaningful
difference, i.e. equidistant). Besides, 60 °C is
hotter than 50 °C (order). However, 60 °C is not
two times as hot as 30 °C and vice versa

Continuous data: ratio scale
 Ratio scale: in this scale, there is an ‘absolute
zero’; therefore, there is a meaningful
difference, and doubling is also meaningful;
besides, the values can be ordered in an
ascending/descending way. For example, in the
Kelvin scale of temperature, 80 K is twice as hot
as 40 K; weight: 60 kg is twice as heavy as 30
kg; and height: 90 cm is twice as tall as 45 cm.

Classification of Data Based on
Source
 1. Primary data: they have been collected from
first-hand experience and are not yet published
and are, therefore, more reliable, authentic, and
objective oriented. The validity of primary data
is greater than that of secondary data, e.g.
information collected through interviews,
surveys, the testing of samples, etc.
 2. Secondary data: they are collected by others

Methods of Collection of Primary
Data
 1. Observational study: a study in which the
investigator observes individuals or where
certain outcomes are measured without
manipulation or intervention;
 2. Experimental study: a study in which
conditions are controlled and manipulated by
the experimenter;
 3. Case study: a comprehensive study of a

Characteristics of Data
 • Accuracy
 • Refinement
 • Precision
 • Reliability
 • Validity

1. Accuracy: it denotes how close or far off a measurement is to its true value. For
example, when a cow’s weight is 350 kg and a weighing machine records the
same, then the measurement is accurate.
2. Refinement: it relates to details in a datum. For example, 350 and 350.25 kg may
both represent the accurate weight of a cow, but the latter is more refined. Increase
in refinement improves the epidemiological value of a descriptive diagnosis, for
example mastitis, mastitis caused by bacteria, mastitis caused by
Streptococcus spp. To increase the refinement of a diagnosis, the application of suitable
auxiliary tests are required; for example, a complement fixation test (CFT) will detect the
types of influenza A virus, but for sub-typing, haemagglutination and
neuramini_x005F_x0002_dase tests are essential.

 3. Precision: it is used in two senses—as a
synonym of refinement or, statistically, to
indicate the consistency of a series of
measurements, i.e. how close or dispersed the
measurements are to each other. Therefore, it
is a function of the standard deviation (SD) of
the data that have been observed. The less the
SD is, the more precise the measurement
system would be. For example, the prevalence

 4. Reliability: data are reliable when a test
produces similar results when repeated. It is
expressed as repeatability and reproducibility:
 (a) Repeatability denotes the agreement
between the results of a test applied on the
same animals/samples many times by the same
observer
 (b) Reproducibility is the agreement between

Sensibility
 it is the proportion of the sick people in the
screened population who are identified as such
by the screening test.

specificity
 is the proportion of really healthy people who
come identified as such by the screening test.

Bias
is a systematic error, which may be due to the design, conduct, or analysis of a
study that makes the results invalid. Important biases are as follows:
1. Confounding bias: an error that causes an incorrect estimation of the association
between exposure and outcome. When present, the association between an
exposure and outcome is distorted by an extraneous third variable,
i.e. confounding variable.
2. Interviewer bias: it is a non-sampling error. Basically, it is human error
(con_x005F_x0002_sciously or unconsciously) caused by preconceived judgement about
an inter_x005F_x0002_viewee, which affects the evaluation of the candidate, negatively or
positively, thereby making an interview less objective and hence unsuccessful. It can
include intentional errors, such as cheating and fraudulent data entry.
3. Measurement bias: it is due to inaccurate measurement (faulty instrument), for
example misclassification of animals as diseased and healthy because of low sensitivity
and specificity of tests.
4. Selection bias: animals selected from abattoirs are unlikely to have a clinical
disease, whereas the general population will have some clinically diseased
animals.

Coding of Data
Data on animals can be divided into two categories:
1. Permanent or tombstone data, which remain unchanged during the animal’s life,
e.g. species, breed, sex, date of birth/death/calving, etc.
2. Descriptors or specifiers, which vary during life, e.g. lesions, test results, signs,
diagnosis, etc
Coding may be done as follows:
1. Numeric codes (represents text in numbers)
2. Alpha codes (letters)
3. Alphanumeric codes
4. Symbols

Important Sources of Veterinary
Data
1. Government veterinary organisations
2. Private veterinary practitioners
3. Insurance organisations
4. Abattoirs
5. Poultry packing plants
6. Knacker yards
7. Serum banks
8. Registries: pathology registry
9. Pharmaceutical and agricultural sales: indirect means of assessment of the
amount of disease
10. Zoological gardens: International Veterinary Record of Zoo Animals, Geneva
(a central registry)
11. Agricultural organisations: BAIF, National Bank for Agriculture and Rural
Development (NABARD), dairy co-operatives
12. Commercial livestock enterprises: Venky’s, Suguna, Godrej, etc

Distribution of Data Set
The distribution of data set means the arrangement of data values, which can be
described by its centre, spread (variation), and overall shape. If the left side of a
distribution is the mirror image of the right side, then the distribution is symmetric,
but if not, then it is asymmetric.
In symmetric data, the mean is used to describe the centre and absolute deviation
to describe the spread,
in asymmetric data, the median is used to describe the centre and interquartile
range to describe the spread.
The distribution of data may be as follows:
• Normal
• Binomial
• Poisson

Normal
is a common probability distribution and is always symmetrical about the mean with a
bell-shaped curve.
The mean and standard deviation determine the
shape of normal distribution;
If the standard deviation is
small, the bell curve will be steeper.
If the standard deviation is large, i.e.
the data are spread far apart, then the
bell curve will be much flatter

Distribution of data
2. Binomial distribution: it relates to discrete data, when there are only two
possible outcomes on each occasion, e.g. sex of newborn—male or female,
success and failure in examination, or head or tail in coin.
3. Poisson distribution: it concerns counts and is applicable when events occur
randomly in space and time, e.g. random occurrence of cases of a disease in a unit
time or a unit area, distribution of a virus particle infecting cells in tissue culture,

Measures of Disease
There may not be a direct measure for health.
Indirectly, the absence of disease in a population may be considered a measure of health.
The measurement of health is expressed in the form of rates and ratios.
Rate refers to the enumeration of an event in a population during a specified time/
period.
It consists of two components: the ‘numerator (the event)’ and the
denomi_x005F_x0002_nator (the population)’. Both have to be defined precisely

Morbidity Measures
There are two essential components: the number of cases in a
population and the specified period of time.
Incidence measures the number of new cases,
prevalence calculates the number of affected.
Both are expressed in relation to the population at risk.
Incidence measures new cases, while prevalence measures total (old + new)
cases at a given point in time. Annual incidence rate (IR) will include only the
new cases reported during the year, while prevalence will report both new and old
cases together. Thus, prevalence gives an overall picture of total number of cases.
Prevalence is dependent upon incidence and the duration of the disease and varies
with incidence and duration.

Morbidity rates
 Specific morbidity rates can be calculated
based on the same pattern.
 If the population is at risk for a limited period

Mortality Rates
These can be the crude death
rate (i.e. the total of all
deaths, irrespective of cause,
age, breed, sex, etc.) or specific
death rates (i.e. deaths
due to specific causes, say
anthrax, specific to sex, specific
to an age group, specific
to breed, etc.). The numerator
consists of the number of deaths
and the denominator,
the average population during the
same period of observation.

Formula for measuring production

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