L2 -Infectious Disease Epidemiology.pptx

Epidemiology

1. Inf e ctious Dise a se Epid e miology By:-Telksew Yelma (B.Sc. Mw, M.Sc. Mw, MPHE) October 24, 2023

2. Infectious disease epidemiolo g y: definition T h e st u dy o f ci r cu m sta n ces u n d er which b o th p o p u la t ion in f ecti o n and dise a se o c cur in a and the fact o rs s p re a d wh i ch a nd in f lu e nce di s tri b ut i on th e ir of fre q u e n c y , in f ecti o us dise a se s .

3. Wh a t is Infectious Disease Epidemiol o gy? In f ectious Dise a se Epid e m i ology E p idemiology • Dea l s with p o p u l a ti o n Risk ca s e o n e – – – Two or mo r e p o p u l a ti o ns A cas e is a r i s k fa c tor The c au s e often k n own • • Id e nt i fi e s c a u s es

4. What is infe c tious disea s e epidemiolog y ? Two or m o re p o p ul a ti o ns • • Humans In f e c ti o us a g e n ts – H e lmi n thes, bacteria, f un g i, protozoa, virus, pri o ns • Vec t or – Mosqu i to (p r otozo a- malaria), sna i ls (helmi n th s - sch i stosomiasis) B l ackfly ( m icrofi l ari a- onc h ocer c i a s is) – • Anima l s – – D o gs a n d sh e e p /goats – E c h i n o coc c us Mice and ticks – B o r r el i a

5. What is infe c tious disea s e epidemiolog y ? A cas e is a ri s k f a ctor … I n f e ction in o ne p erson can be tr a nsm i tt e d to ot h ers

6. What is infectious disease epidemiol o gy? The c a u s e oft e n k n o wn • – An infecti o us a g e n t is a n e ces s ary ca u se What is i nfe c tious dis e a s e e pidemiology used f or? • Id e nt i fi c at i on of cau s es of n ew, em e rg i ng I n fe c ti o n s , e. g . H IV, SA R S, Swine fl u ,Eb o la Sur v e i ll a n c e o f i nf e c t i o us d i s e a s e Id e nt i fi c at i on of s o u r ce of o u tb r e a ks Stu d i e s of r o u tes of tr a n s mis s i o n & n a tu r al h i s t o r y of in f e c ti o ns Id e nt i fi c at i on of n e w i n te r v e nt i o n s • • • •

7. Transmission Cases • • I n d e x – t h e first case i d e n ti f i e d Prim a ry – the case th a t bri n gs the a p o p u la t ion i n fecti o n i nto • • Sec o n d ary – i n f e cted Tert i ary – in f ected by by a pr i m a ry a seco n d a ry case case o o o o Sus c e p ti b le Immu n e Su b - c l i n i c al Cli n i c al

8. • Natural History of Diseases

9. Natural Hi s tory of of Dise a ses Ref er s to the pr o gr e ssion a dise a se pr o c e ss in an i n d i vid u al ov e r t i m e , in t he a b s e nce of in t erven t io n .

10. Time course of a disease in relation and communicability to its clinical expression Clinical case Symptomatic Asymptomati c TIME 1 st manifestation of disease (clinical onset) Agent starts being shed Recovery Agent stops Relaps Time of infection (biological onset) Latent period Incubation period Communication period Prepatent Generation period b e i ng s hed e Clinical Threshold Chronic As y mpt o m at i c carri e r ca r r i er

11. Time lines f or infections

12. Dis e a s e Tran s mi s s i on from Infe c tious host to su s c e ptible host I n f e ctio u s Host Sus c ep t ib l e Ho s t Con t act Tra n smis s ion d e p e n d s o n: -in f ecti o us h o st -sus c e p ti b le h o st -cont a ct d e fi n iti o n -in f ecti o us a g e n t

13. Estimating the Transmiss i on Probabil i ty The of p r ob a bil it y that will su c c e s sful tr a nsf e r t he a g e n t o c c ur so th a t the su s c e ptible host be c om e s infe c te d . Two comm o n ways of esti m at i ng tra n smis s ion pr o b a bi l ity ar e : • S e con d ary at t ack rate • B i n o mi a l Mo d el

14. Secondary A t tack Rate n e w cases of kn o wn A m e asure of the fr e q u e n cy of a d i sease a m o n g t h e con t acts cases. of • F irst in f ecti o us ( in d ex case ) in d ivid u als a re id e nt i fi e d N u mber of p ersons e x pos e d (have contact w i th a kno w n case) who dev e l o p dis e ase X 1 n S A R = T otal number of s uscept i ble e x pos e d person

15. Binomial Model of Transmission Probabil i ty Nu m ber of s usc e ptible who become inf e c t ed T o tal n u m b er of contac t s with infe c ti v es •Su s c e pt i b l e a r e i d e nt i fi e d a nd u s u a lly u s ed wh e n th e y ma d e mo r e th a n o ne p o te n ti a lly i n fe c ti o us c o nt a c t s •The n u me r at o r is t h e same as for SA R . •De n omi n at o r i n c l u de the to t al n u mb e r of p o te n ti a lly in f e c ti o us c o nt a cts th a t s u s c e pt i ble in d iv i du a ls ma k e

16. Bin o mi a l … • The with The p r o b a b il i ty of tr a n s missi o n d u ri n g a c o nt a ct a s u s c e p ti b le an d a n i n fe c ti o us perso n i s p . p r o b a b il i ty of the s u s c e pt i b l e pe r s o n e s c a p i ng • i n fe c ti o n d u ri n g c o nt a ct is q ( o r 1 - p) . • If a sus c ept i ble ma k es n con t a c ts with an inf e c t ive or with diff e r e nt inf e c t iv e s and each the c o nta c t is indep e nd e nt of t h e othe r s, prob a bili t y of e s c a ping inf e c ti on f r om all n q n = ( 1 - p ) n . p o t e nti a l inf e c t iv e s is • The p ro b ab i lity of be i ng in f e c ted aft e r n c o nt a cts is q n = 1 - ( 1 - p) n . 1 -

17. Bin o mi a l … E . g .. – A Stu d y of HIV t r a n s mis s i o n was c o n d u c ted in a po p ul a ti o n b e g i n n i ng , of 100 st e ady sexual coupl es . A t the one c o u p le was a l r e a d y i n fe c te d . 25 b e c a me i n fe c te d . The to t al c o nt a c t s was 1500 . n u m b er of sex u al what i s pr o ba b ili t y o f be i ng in f e c ted aft e r 2 c o nt a ct s . – 1-(1-p) 2 = t h e p r o b a b i li t y b e i n g i n fe c ted – P = 25 / 15 0=0. 16 – 0. 34

18. Leve l s of Dise a se Occurrence 1. Exp e ct e d Le v els • • • End e mic Hyp e r-end e mic Spor a dic 2. Ex c e s s o c c urren c e • Epid e mi c /Outbre a k • Pa n d e mic

19. Ba s ic Repr o d u ctive N u mb e r ( R o ) • R o is the ex p ected number of n e w in f ectious ho s ts (cas e s) t h a t o ne infectious c a se w i l l pro d u c e d u ring the period of infect i ou s ne s s. The v alue of R o is n ot sp e cif i c to a n age n t, but to a n • ag e nt p o pulat i on w i t h i n a part i cular h ost pop u lat i on at a particular t i me. In f ection w i ll ….. dis a pp e a r , if R o < en d emic, if R o = 1 1 ep i demic, if R o > 1

20. What determines R ? • P, t r an s m i ssion prob a bil i ty p er ex p os u re – de p en d s the i n fec t i o n on HI V , p ( h a nd shak e )=0, p ( t ransfus i o n )=1 i n terventions of t en aim at reduc i ng p  • use g l oves, screened bl o od C, number of c ontacts per t i me u nit – relev a nt contact d e p e n d s on infecti o n S a me room, w i thin sne e zi n g distanc e , skin contact. i n terventions of t en aim at reduc i ng c Isolati o n, s e x ual absti n ence   • D, d u ration of infectious p e riod be reduced by m ed i cal i n terventions (TB) w i l l HIV t r eatment a f f ect R in a pop u lat i on? M ay How

21. Effective Reproductive Number (R) • R u n li k e R o a s sumes that all conta c ts by the infe c ti v e c ase a r e not with susceptible individual s . • Thu s , R= R o x ( pro p ortion of sus c ept i ble p o p u la t ion) Example: if R o is 9 and 5 % of the po p ulation is immu n e R= 9 x 0.5 = 4 . 5 So e f f e c t iv e ly a c a s e of the dis e a s e will p rod u ce o n ly 4.5 c a s e s

22. r r M ethod for prevention and control of i nfectious diseases 1. • • In c re a s i ng ho s t re s i s tan c e