Detailed program and plan of the full-time studies
|
|
- Lionel Jared Palmer
- 5 years ago
- Views:
Transcription
1 EHESP School of Public Health Master of Public Health Detailed program and plan of the full-time studies EUROPUBHEALTH Specialization: Advanced Biostatistics and Epidemiology ACADEMIC YEAR Master of Public Health Directory: Dr. Martine Bellanger MPH Course Director Dr. Moise Desvarieux Academic coordinator of the track Advanced Biostatistics and Epidemiology track
2 TEACHING PROGRAM ON HIGHER EDUCATION LEVEL The European Public Health Master (Europubhealth) Classes conducted in 2014/2015 academic year SPECIALIZATION: Advanced Epidemiology and Biostatistics Program of the second year in the Europubhealth programme for French and international students conducted by the EHESP School of Public Health (Rennes and Paris), France. For the first year of the Europubhealth program students basic acquisitions on public health being conducted at University of Sheffield (Sheffield, Great Britain) or in Andalusian School of Public Health, University of Granada (Granada, Spain). The MPH of EHESP is validated for a 4-year period ( to ) by the Agency for Public Health Education Accreditation (APHEA), 1st specific accreditation system for education in public health at the European level.
3 Study plan in Advanced Biostatistics and Epidemiology # COMPULSORY Modules titles ECTS Upgrading Biostatistics Not credited 203 Advanced Core curriculum Epidemiology Advanced Core curriculum Information sciences and biostatistics Advanced Core curriculum Environmental and occupational health sciences Cross-disciplinary Module: Global Health 3 Total Compulsory Modules (1) 12 MINORS 2 out of 3 minors EPI 6 electives with a minimum of 4 in EPI be chosen among minors and majors: ELECTIVE Modules titles ECTS EPI Minor 210 Infectious Disease Epidemiology 3 EPI Minor 211 Chronic Disease Epidemiology 3 EPI Minor 238 Perinatal and Pediatric Epidemiology Biostats Data Mining 3 MAJORS 3 EPI Major 223 Design, Concept and Methods in Epidemiology : compulsory 3 Major EPI EPI Major 224 Analysis in Epidemiology (II) 3 (224 or 225) EPI Major 225 Analysis in Epidemiology (I) SAS Software Biostats Major 230 Multi-level Analysis 3 TOTAL Elective modules 18 OVERALL COMPULSORY + ELECTIVE MODULES : (3) + (2) = (3) SUPRA 215 Biostats Intro to R: computing, graphics and statistics 229 Biostats Modelling of infectious diseases 231 Biostats Spatial statistical analysis OR ANY MINOR & Major of interest in other track 30 ECTS PASS/FAIL MINORS 2 Minors BIOSTATS 1 out of 3 EPI Minors MAJORS 2 OUT OF 3 Major Biostats 6 electives with a minimum of 4 in Biostats be chosen among minors and majors ELECTIVE Modules titles ECTS Biostats Data Mining 3 Biostats Intro to R: computing, graphics and statistics 3 EPI Minor 210 Infectious Disease Epidemiology 3 EPI Minor 211 Chronic Disease Epidemiology 3 EPI Minor 238 Perinatal and Pediatric Epidemiology 3 Biostats Modelling of infectious diseases 3 Biostats Multi-level Analysis 3 Biostats Spatial statistical analysis EPI Major 223 Design, Concept and Methods in Epidemiology 3 TOTAL Elective modules 18 OVERALL COMPULSORY + ELECTIVE MODULES : (3) + (2) = (3) SUPRA 224 EPI Major 224 Analysis in Epidemiology (II) 225 Major 225 Analysis in Epidemiology (I) SAS Software OR ANY MINOR in EPI not taken or any MInor & Major of interest in other track 30 ECTS PASS/FAIL EUROPUBHEALTH INTEGRATION MODULE RENNES 2 INTERNSHIP - THESIS 28 Total (4) 30 ECTS MPH Year 2 : (3) + (4) 60 ECTS
4 Syllabus Advanced Module of Epidemiology Module 2O3 Advanced Module of Epidemiology UE coordinator Dates Credits/ECTS Duration Module description Prerequisites Course learning objectives!"#$%"$! &"' ( ) *+* )*,%-./0( * + # *1 *& # * 1 %# * 1 7 %# *1# 8 * & 9 % : ; *1 # # * ## ( # # < % % # # # % % % 8 = &
5 # # % ; # % UE structure (details of sequences : title /speaker/date/duration ) 7 * ## -=>3=42? # -= >4/=4@?* 4*&A 3B2B204/.00 2* < $ 3B03B204/.00 -*C C3B4.B204/.00 /* DA# 3B2-B204/.00 5* ED ' 03B-0B204/.00 Course Requirement Grading and Assesment Location # * #*,% # * # # ; # *' * 1 #% >** *?! * #* % # ; * 1 '; #% ; % * F% # #9< '*: ; # # * # ( 4* ' >20G? 2* #%>-0G? -* A >50G? F B' / H@500.'& Readings 1I1DJJC( F'* *2*KED +200L*
6 M4 % J!"#$%"$! &"' (40L)* * J#A < J7 ; &E # ;D N #% > ;?' N 1 '. 1 43=4@ A A E (*--=-.-3=52F%( 4=-*-=2. E ( 45-L-=/03 ( & O5! % < $ " #! $ ( # ) * J J# 8 < J7 % # # # + # = = + # = # =
7 # 8 # * % & ' 8 #; 8 8 ; 1 '. 1 0L3=4@ A A E ( 4.*/44=/-0/-2=//0 ( O- % J % ' C C! "#$%"$! (%%240/) * J# < J7 % ' %! =! =! = % ' ( % F %# ; & %>? %>?! % ' % # # 8 & < =4@
8 1 ' A A E (.*4/3=45@ 3*223=2/22/5=2/3 25/=2.0 E (.*4/5=4/3 L*204=244243=222 22/=22L+ E (.*4.0=4./ 4/*-5@=-L2+ 8%E"*4/=43 ( = O/ % J ) DA# D E! "#$%"$! (#4) * J# D *& & < J7 ) # # 8 # '8# =; # * &# 8 < 8 * == # ' =4@ E ( 44*2L@=23@-00=-05 E ( 40*2.4=2L. (' 81 M5 % * '!
9 "#$%"$! (240.) ** * J J# 1 < J7 & F + # * ( o o & # 8 1 ' =4@ A A E ( D
10 O5! % J D<% >?! (4) * J# 8 < J7 % # # # + # = = + # = # = # 8 # * % & ' 8 #; 8 8 ; 1 ' =4@ A A E ( 4.*/44=/-0/-2=//0 (
11 !" 7! 8)8!8! 9 Emilie Counil!"#$ %&!!!' ()*!+,! -"!!!-!-!)*!+ *!!!! +! +. "/! -.* 0 0*1! +. * *) ++*!!! +. 0!* )!! * )+2 "*!!*!!!-! + +!**!- /!)*!+! + %!.* + +!/ *+*!! +!3- * + & 4 0!!!!5 %- + &)! " 0 0*1 %! 6 5%! + + :!!"/!/# 5;! +/<+ + :!!"=//!/# 5;! +/ " :!!"=//!/# 5;! +/% :!!">=//!/# 5;! //<*;?- :!!"@=//!/#
12 #$ %!$ %! -!. & '! 4,!
13 ) < +?C - D +! (( &50+! /B%? 0! + 0!!!5 A-- * +! <5B / ) < +?C - D ) < +?C - D +! &!! <5E- D+ D%/B%? 0 -!+ 0!!!5 / "+ + " /! *,!!* /! - " /!! <5+ + ;! * &5E- D+D -!+ 0!!!5 /!! " /! "!!* # <5 " ;!
14 0 0* ) < +?C - D +! &5E- D+D -!+ 0!!!5 /! /!!! " # <5 8! ;! +5! " 0 0* # )$* ) < +?C - D +! &5E- D+D -!+ 0!!!5 2 ", "!! ")! # <5!*;?- "! " ;! +5! 0 0*
15 Syllabus Module 206 *&$ &7) + Core curriculum, Environmental and Occupational Health Sciences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
16 # 0-+ &$ 3!$! '( $2*!!& &#$#'$- ( '$ #D+/ : &2&/ 6 1)!!& &&/8!'.' '= #/ <C#>'C< 8E)/F,/C!>&&;>&& 2) &&'#3#&!/<) 1 )A (=/ -$ G 3)?-!&'# $! $ 185C
17 ! "# $ & $ 5 = 6 = =!"#$!#%!& # '( ) (& *+,*-%*./0 123! +& / 6 & &7& & * & && # % $ ( % % % 8 % % % $% 9 & :( % (! & # ' # ( # ' ; & % 5 /( 8 && & 9< : *( & & & 7 1( # ' & % # /( > ( 5 *+ * *(?(@ 5*+* 1( < ( 5 *0 * A( <7 #( < 5 *0 * +( ; % 2(;( 5*B* 0( $ #( < 5 *B * B( > #( 5 *C 1 C( 8 (;D 5 *C 1 -( <7 & ( 5 *-* /.( 3 6E ( % (
18 & 5 6 B //(! ( ( 5 *- 1 #% % ; % & 6 & & 6( > & 5/..F & & ; % %!## ' ; G; ()*(+( 3 & & 6 ( ; < H6 6 < & ( ((,(-. / /!! 3 && & E&& 6&% & (; & (3 (G I J 7 8 % & & & ( (*(+( 3 6 & &7% 5 & 5-2 % & 5& && -? 5 %&% -? 5 % % % - > 2 < 5 - J7 7 - G6 % % - - (0*("!!( (1*(2(3 (4*("!!( (5*("(6 & 7 &/. ' 8 9: 32$ # %#& &, K # C,?,! 3,! 7!, ' && &
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
20 Syllabus Module Minor A: 210 Module 210 Infectious disease epidemiology UE coordinator Andrea A. Howard, MD, MS Associate Professor of Epidemiology Mailman School of Public Health, Columbia University New York, NY, USA Dates 19 to 23 October 2015 Credits/ECTS Duration Module description 3 ECTS 5 days Infectious disease epidemiology studies the occurrence of infectious diseases; factors leading to infection by an organism; factors affecting transmission of an organism; and factors associated with clinically recognizable disease among those who are infected. It requires the use of traditional epidemiologic methods as well as methods unique to infectious disease epidemiology, such as mathematical modeling. In addition to knowing epidemiologic methods, infectious disease epidemiologists need to be familiar with the biological features and clinical manifestations of important pathogens as well as laboratory techniques for the identification and quantification of infectious organisms. This course is designed to provide an introduction to infectious disease epidemiology. It will focus on the tools and methods used in identifying, preventing, and controlling infectious diseases to improve public health. Case studies based on the literature and the work of faculty members will be used to illustrate the real-world application of these tools and methods to address public health problems. Prerequisites. Course learning objectives UE structure (details of sequences : title/speaker/date/duration ) Students who successfully complete this course will be able to: Discuss the key concepts of infectious disease transmission and control, and the differences with non-infectious diseases Apply biological principles to development and implementation of disease prevention, control or management programs Specify the role of the immune system in population health Apply epidemiologic tools and methodologies to understand the transmission dynamics and control of infectious diseases Critically appraise and interpret the findings of infectious disease epidemiology papers Specific leaning objectives are noted for each session. At the end of each session, students should know and be able to accomplish the session s learning objectives. Session 1. Introduction to Infectious Disease Epidemiology Session 2. & Evaluation of Diagnostic Tests and Treating Latent Infection as a Control Strategy: Tuberculosis Session 3. Causal Inference, Mathematical Modeling, and the Development of Public Health Policy: Voluntary Medical Male Circumcision to Prevent HIV Transmission Session 4. Epidemiology and Control of Malaria Session 5. Epidemiologic Methods for Measuring Transmission and Control of 1
21 Respiratory Infections: Influenza Session 6. Epidemiologic Methods in Vaccinology Session 7. Choosing Biologic Outcomes and Developing Immunization Policy: The Human Papillomavirus Vaccine to Prevent Cervical Cancer Session 8. Mathematical Modeling: Introduction to Concepts in Transmission and Dynamics Session 9. Epidemiologic Methods for Measuring Transmission and Control of Viral Hepatitis Session 10. Surveillance and control of healthcare-associated infections Course requirement Grading and assesment 100% Final written examination Location Columbia Global Centers\Europe, Reid Hall 4 rue de Chevreuse Paris Readings assigned journal articles 2
22 1 Session Title Introduction to Infectious Disease Epidemiology Speaker Session Outline Andrea A. Howard, MD, MS Associate Professor of Epidemiology Mailman School of Public Health, Columbia University New York, NY, USA Overview of the Biological Basis of Infectious Disease Epidemiology, Immune Response, and Methods for Detection of Infectious Diseases Application of Fundamental Epidemiological Study Designs to Infectious Disease Learning Objectives Describe the host-pathogen-environment interaction and identify biologic factors influencing this interaction Summarize the epidemiologic classification of infectious diseases Explain the natural history of infectious diseases Demonstrate the role of transmission mechanisms in disease control and prevention Describe the branches of the immune system Explain the different immune responses to specific infectious diseases Describe laboratory testing methodologies used to monitor or detect infectious diseases and determine susceptibility to pathogens Apply traditional epidemiological study designs including cross-sectional, casecontrol, and cohort, for the purpose of investigating infectious disease transmission Compare the respective strengths and limitations of these traditional epidemiological study designs Explain the assumptions of traditional epidemiological study designs that limit their use in studying infectious disease transmission Duration Dates Training methods 3 hours Monday October 19, 9h-12h Face to Face Reading Validation Not applicable # 2 Session Title Evaluation of Diagnostic Tests and Treating Latent Infection as a Control Strategy: Tuberculosis Speaker Andrea A. Howard, MD, MS Associate Professor of Epidemiology Mailman School of Public Health, Columbia University New York, NY, USA aah2138@columbia.edu Session Outline Learning Objectives Describe how knowledge of the epidemiology of an infectious disease can be used to choose a cut-point for a diagnostic test Calculate the sensitivity and specificity of a diagnostic test 3
23 Determine the predictive value of a diagnostic test given the prevalence of disease in the population Outline limitations of the use of various tests for the diagnosis of latent tuberculosis infection and identify settings in which use of specific tests or cutpoints would be useful Evaluate strategies for TB control that target people with latent TB infection Duration Dates Training methods 3 hours Monday October 19, 14h-17h Face to Face, Group Work and Student Presentations Reading - Cailleaux-Cezar M, de A. Melo D, Xavier Gm, et al. Tuberculosis incidence among contacts of active pulmonary tuberculosis. Int J Tuberc Lung Dis 2009;13: Golub JE, Pronyk P, Mohapi L, et al. Isoniazid preventive therapy, HAART and tuberculosis risk in HIV-infected adults in South Africa: a prospective cohort. AIDS 2009;23: Assignement Come to class prepared to discuss the following: 1) Based on the data presented by Cailleaux-Cezar et al., do you think the Brazilian government should change its criteria for LTBI treatment? If so, how? What data support your answer? If not, what additional evidence would you require? 2) If clinical trials have shown that treatment of LTBI reduces TB incidence among HIVinfected individuals, why did Golub et al. conduct this study? Why did they use the chosen study design? How might the effect size change if TST-testing was not performed? # 3 Session Title Causal Inference, Mathematical Modeling, and the Development of Public Health Policy: Male Circumcision to Prevent HIV Transmission Speaker Andrea A. Howard, MD, MS Associate Professor of Epidemiology Mailman School of Public Health, Columbia University New York, NY, USA aah2138@columbia.edu Session Outline Learning Objectives Describe the biological properties that appear to promote HIV acquisition in uncircumcised men compared to circumcised men Apply criteria for causality to determine whether a biomedical intervention prevents acquisition of an infectious disease Define risk compensation and explain how it can impact the effectiveness of a prevention intervention Interpret the results of mathematical modeling papers to determine whether a public health intervention will lead to reductions in infectious disease transmission and prevalence Duration 3 hours 4
24 Dates Tuesday October 20, 9h-12h Bailey RC et al. Male circumcision for HIV prevention in young men in Kisumu, Kenya: a randomised controlled trial. Lancet 2007;369: Hallett TB et al. Understanding the impact of male circumcision interventions on the spread of HIV in southern Africa. PLoS One 2008;3:e2212. Londish GL, Murray JM. Significant reduction in HIV prevalence according to male circumcision intervention in sub-saharan Africa. Int J Epidemiol 2008;37: Assignement Come to class prepared to discuss the following: 1) Applying Hill s criteria for causality, what is the evidence that male circumcision prevents acquisition of HIV? 2) In deciding whether and how best to include voluntary medical male circumcision as part of a HIV prevention program, what are the key questions to be addressed? Which of these can be answered using the clinical trial data and which are best answered by mathematical modeling? # 4 Session Title Epidemiology & Control of Malaria Speaker Session Outline Dr. Jacques LeBras Institut de Médecine et d Epidémiologie Appliquée/Institut de rechercher pour le developpement (UMR 216 IRD) Paris Epidemiologic Methods for Measuring Transmission and Control of Vector-borne Infections: Malaria Learning Objectives Discuss the limitations of epidemiologic methods used to measure the burden of malaria in the population Describe the control strategies used for malaria Duration Dates Training methods 3 hours Tuesday October 20, 14h-17h Lecture Reading Validation NA for this session, final written exam on November # 5 Session Title Epidemiologic Methods for Measuring Transmission and Control of Respiratory Infections: Influenza Speaker Andrea A. Howard, MD, MS Associate Professor of Epidemiology Mailman School of Public Health, Columbia University New York, NY, USA 5
25 Session Outline Learning Objectives Identify sources of surveillance data used to monitor influenza activity, and the ways in which these sources can be biased Describe available influenza mitigation strategies, and how they affect transmission Describe how complexity can be added to basic SIR models for evaluating pandemic policy strategies Describe how model assumptions can alter the interpretation of model output Discuss strengths and limitations of study designs used to assess the effect of herd immunity from influenza vaccination Duration Dates Readings 3 hours Wednesday October 21, 9h-12h Khazeni N, Hutton DW, Collins CIF et al. Health and economic benefits of early vaccination and nonpharmaceutical interventions for a human influenza A (H7N9) pandemic. Ann Intern Med 2014;160: Loeb M, Russell ML, Fonseca et al. Effect of influenza vaccination of children on infection rates in Hutterite communities: a randomized trial. JAMA 2010;303: Assignement Come to class prepared to discuss the following: 1) What kind of influenza mitigation strategies are available, and how might these interventions affect transmission (think of this in terms of the equation for R0)? 2) In the paper by Khazeni et al, what assumptions did the authors make? Do you think they were reasonable? 3) What are some of the strengths and limitations of the study design chosen by Loeb et al? # 6 Session Title Epidemiologic Methods in Vaccinology Speakers Judith Mueller Lecturer Departement EPI & Biostats EHESP Judith.Mueller@ehesp.fr Session Outline Learning Objectives Explain the principle epidemiological concepts around vaccine prevention Describe study designs for evaluation of vaccines and vaccination strategies Explain the role that vaccination can play in the occurrence and prevention of epidemics Describe a selection of immunization programs (polio, pneumococci) Duration Dates 3 hours Wednesday October 21, 14h-17h 6
26 Training methods Lecture Reading Validation NA for this session, final written exam on November # 7 Session Title Choosing Biologic Outcomes and Developing Immunization Policy: The Human Papillomavirus Vaccine to Prevent Cervical Cancer Speakers Andrea A. Howard, MD, MS Associate Professor of Epidemiology Mailman School of Public Health, Columbia University New York, NY, USA aah2138@columbia.edu Session Outline Learning Objectives Explain human papillomavirus (HPV) natural history and its link to cervical cancer Discuss how the diversity of HPV types necessitates development of broad spectrum immunologic vaccines Discuss the strengths and weaknesses of various biologic outcomes used to evaluate efficacy and effectiveness of HPV vaccination Design studies to assess the impact of HPV vaccination programs Duration Dates 3 hours Thursday October 22, 9h-12h Reading Joura EA, Giuliano AR, Iversen OE, et al. for the Broad Spectrum HPV Vaccine Study. A 9- valent HPV vaccine against infection and intraepithelial neoplasia in women. N Engl J Med 2015;372: Markowitz LE, Hariri S, Lin C, et al. Reduction in human papillomavirus (HPV) prevalence among young women following HPV vaccine introduction in the United States, National Health and Nutrition Examination Surveys, JID 2013;208: Assignement Come to class prepared to discuss the following: 1) In the papers by Joura and Markowitz, what were the endpoints? What was the rationale for choosing each endpoint, and what are the limitations? 2) Why weren t Markowitz et al. able to assert that there was evidence of herd immunity in their study? 3) What are some of the other studies that could be conducted to assess the impact of HPV vaccine on HPV infection and disease outcomes? # 8 Session Title Mathematical Modeling: Introduction to Concepts in Transmission and Dynamics Speaker Session Outline Pascal Crépey, PhD, Lecturer Departement EPI & Biostats EHESP Pascal.crepey@ehesp.fr Introduction to concepts in transmission & dynamics based upon mathematical modeling 7
27 Learning Objectives Describe in words, by diagram, and by differential equations a basic compartmental model (like the susceptible-infectious-recovered [SIR] model) Identify the parameters to calculate the basic reproductive number (R0) Explain the concept of and calculate the epidemic threshold Describe in words and mathematically the effect of vaccination on the spreading of a disease in a population Provide examples of control strategies for the transmission of infectious diseases, and what transmission parameters are targeted by these strategies Identify how and why epidemics behave differently in closed versus open populations Identify the limitations of deterministic models, and characteristics of infectious disease transmission that may limit their use. Duration Dates Training methods 3 hours Thursday October 22, 14h-17h Lecture Reading Validation NA for this session, final written exam on November 26 or 27, 2015 # 9 Session Title Epidemiologic Methods for Measuring Transmission and Control of Viral Hepatitis Speakers Andrea A. Howard, MD, MS Associate Professor of Epidemiology Mailman School of Public Health, Columbia University New York, NY, USA aah2138@columbia.edu Session Outline Learning Objectives Identify appropriate prevention strategies for viral hepatitis based upon the epidemiology of the disease in the targeted population Evaluate the impact of Hepatitis B vaccination strategies in the US and globally Assess the impact of risk behaviors and preventive measures on HBV and HCV prevalence Duration Dates Reading 2 hours Friday October 23, 9h-11h Burt RD, Hagan H, Garfein RS, Sabin K, Weinbaum C, Thiede H. Trends in hepatitis B virus, hepatitis C virus, and human immunodeficiency virus prevalence, risk behaviors, and preventive measures among Seattle injection drug users aged years, J Urban Health 2007;84: Liang X, Bi S, Yang W et al. Evaluation of the impact of hepatitis B vaccination among children born during in China. J Infect Dis 2009;200: Assignement Come to class prepared to discuss the following: 1) What were the outcomes used to determine the effectiveness of Hepatitis B vaccination programs in the paper by Liang et al? What are the pros and cons of each approach? 2) What risk behaviors and preventive measures were assessed in the paper by Burt et al? How could differences in study design among the included studies have influenced the findings? 8
28 #10 Session Title Surveillance and control of healthcare-associated infections Speaker Pascal Astagneau, Departement EPI & Biostats EHESP Session Outline Method of health care associated infection control programs and surveillance will be presented. Comparative analysis of interventions regarding human and economic resources required for data collection and patient follow up will be discussed in terms of cost effectiveness. Learning Objectives Identify different programs for controlling health care associated infections worlwide Compare different surveillance systems in terms of cost effectiveness Describe the limitations of surveillance systems that rely on routine data collection, for instance in hospital settings Duration Dates Training methods 4 hours Friday October 23, 13h-17h Lecture Reading Assignement NA for this session, final written exam on November
29 !"# $ %!"#$%!"!% &'(()##('"*!####($+#(! )#*++#)(*$,'((+%"+!+#!!++(' +#!)(+#"+#!#(-*###($!" )(*$"-"#+, )+"+!'((#(+!+#)(*$" +#+%#+#+-#*'.+)!#"-.))!(#!!#(-. +#+''(.+#+#.+#+.-"#+"+#+. )(*$"/##+!(##0/1././'(./#.- "#+, +!-$++)"++##"$(#-"#+, )+"$("*+#))#+"++#, ))($)(*+(#(*"++#!+#+#+#/ 2, "$-$)")(*###($#$#+', ))($)##+)(*$(+++##, /+#(($##)"*"++#)(*$)#) 3+!'-)(*$# #+*($+!#*, ++(!"+!#4##'((#*+*+!+,& 4##'((#+#"!()(++!5"#(##$6!, 7 3/#)!3#
30 &( )#- 8#*9:+ &$!'( &(# /(!#$ 7 3 "!'((#(% ; "#<++#=##))+#+)(4""*#" ; >#'#"(#*+#!"#*(#(($ ; "$)#++#-"#+ ; "$+++#$ ; &"#(#?')(*$"+##+!(##*(#(($#'((#)#- "#+!#! # #* &( )#- &&(( /(!#$ 7 3 "!'((#(% ; "$)###!))#"(##$###$(# ++# ; /#(+!(#)#*#)+#(!#) ; >#'#"(-(##!($##((-""+"+(+#(!#!($!#! # #* #+-#(,&)#"#*+##,
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
34 &( )#- 8#*9:+!# # ("G& /(!#$ "!'((#(% ; +#+++)"+#+*#+#+)#(*$##))+#(+#+ +#!#! ; #!#*"!+#++*#+)(4#'((#+! #))#++* ; +!-$##!!$*##)#++#)(*$ )+#(($+#+)(*$ ;!#?#+-"#+#)!#(+#+(*$#)#'((#'!$++#)(*$! #* #),+ +*">#/#+"##?&#(,/#+DII, +F7,#(, +*#3#;/#+#($##?!)#!$,A D, 7,#(,+#+#"#*#,ADI, >#($,#(,7)#+((!(#/#+##7)#>!,&8#+DE, 79C(#,"()#;&+)(>#/#/#+3!$G!),& ""+"##>#/#++"8!*/#+#9/#+#( -,ADD2,!*!,,)(*$#3, 7'?,CF,(##($+"/#;/(!"*# #(/#+,ADIE, >(+-G,'"#(#"#$,+#A!#(")(*$ DE, +#?-,8#+-"""+"#8';F#7*;F+!+"/(+#(#, A,
35 !"#$$%&'()%)%))%)# *'%+,-)$%&) )))#(-)%*-+./).))012)3-)1. )))%(#*+.% -45" 6 "!75"-8 9:;""*7+6<<"""!! (:;""*7+="4 6!>45 8:;""*7+6<<766=4! :?(@$? <(67! "(67!! "# *) ))E$2E)E)+ "-9 534?!A"7 )$)$&3B&))$&3B)) )3))$)? 9C'C: 9&)$)))$)$)$&3 &$))):$)())$& )))$$)()))) $)?.(0)0(&&) &$&3?.'9': &)00$&)?))3&0( )&)02)&)?$& $)0(00)$)8$&&)) ))3)3&(? )))$&3 ))0$))0((): D)23$)$)$)$&3 D.$$3$&))&))))$) $)) D-)3$$)$))&$)$)$&3$$ :))))0()) 2B3$) 3< " 5 4"7 :F()))$&3 G3< " 5 4"7 : ))) G3< " 5 4"7
36 :)()0()0&) 3< " 5 4"7! $ % & ')0))0$))33(3)) $2?9)0()02?)3&)(3 ))$20$)$$))3)))30))8$)? ))002&)?930$))&)))3 )02?'0())8$)&)))(&&)02? ))0)0))0))$)$$$)3) $$?.80(&? F&: 6!H))$)) 6!H)&)$)3!7H)8))( -$ )&3)0($).$))?
37 9) 3 $2 ' () *+, *-. ++ %:?(@$? &'(/) )23$)))()).$$3$&))& -)3$$)$))&$$) ) 4?! 9&) < $65$:&:)))02G)))0) $)))0)&))3) 5:77!:"7$:G)))0)$)))0 )&))3,020))B$ #) 9) G3 $2 $ /+ %:?(@$? '# --)6 =)-))9$ &'(/) )23$)$)$)$&3))))&.$$3$&))&))))$) $)) -)3$$)$))&$)$)$&3$$ ))))$&3 ) 4?! 9&) < $:) 6:77 :77$5:77!:"7$:G)))0)$))) 0)&))3,020))B $#) 6"$:)$20))) "5$:.&$))0$))))$2
38 9) 93 $2 *+, # %:?(@$? '# - -%-9$&)$) $) IJ)))'())))$&3 9-)$&3 )))!" &'(/).$$3$&))&))))$) $)) -)3$$)$))&$)$)$&3$$ ))()) ) 4?! 9&) < 7 6:77 :77$5:77!:"7$:G)))0)$) ))0)&))3,020) )B$#) 7 :)$20))) 6:.&$))0$))))$2 6"$:)$20))) "5$:.&$))0$))))$2 9) 3 $2 + %( + 0+ %:?(@$? '# -1.<!"9)):)&3# $))) &'(/) )23$)))$)()$)$&3 -)3$$)$))&) ) 4?! 9&) < 7 6:77 :77$:G)))0)$)))0 )&))3,020))B$ #) 7 :)$20))) 6:.&$))0$))))$2 6!:"7$:))02)
39 ! "#$" %&' ()'()%* +!,#-&.+) /##///-#/#" /-00//-##//" /0//-#0-1//-/##/ /-///2/#2 ##2"0//# /"-/#/##// #" #-##/3-#"!" #$ 5#/ /676#6#8 " % ## - /3#4//-//-" - //#3 - //#/// //#///###" -%4#/#/# 9 /!/-0/ :#-'%; <4))%(4))#%4)) *4)) -(4/!/- / #-'%= <4))%(4))#%4)) *4)) -+4!//-/ >##-'%< <4))%(4))#%4)) *4)) -*4!//-/ #-'() <4))%(4))#%4)) *4)) -,4/2?#-'(% <4))%(4))#%4)) *4)) #3//2#0/-1#/// #"-3//#/#/" ##/2 /#-#/
40 & ' % 7 9B #!/@//!6A#//*A#! ' Introduction to multidimensional methods 94! "#$" - #/3#/#/ - #/#/ - //-#/ %( 94#/#/#/!/- 0/!%4//4/###2 /0//-"!(4//4 /-04/!/2 3 ( Cluster analysis 7 9B # &4 "#$" - #///- - #//-##3## - ####// - / %( 94!//-5//### /8!%4//4C-#D1#/ 2//3##?!(40/-9-/ 3
41 ! " #!$% &!!" #$ % & '( )#' * + '(()*() )*))(((+ ())()*)+ &()*),-)*+(.()),)*)( ()*)+ )*)/,0()) 1()## 1).()*))* )*) &0((()* ),(,/ (( 2(()*((*( 3(4( '(())* ))*( 5*4)0()*) )(4)(, 0-/ 4- ) 6+ &()*/ ) ) ) * #!$ 35,4)/&()*/* )+30)/,9-#!!:+ &,()0()))* + *)),-*)0, )+ &&(
42 (- 8*3. &&&& )))/ ; (( ; &0(;(()*) ; '(() ; )-))) ; (* *) 5)* (,)),-))* )*)0()*)+)*), ))((+ )<<(,,, ()*)< -))))) -)))-) ()(+ ')*)-, ))0(,-= 0(/"> (+>"(($ (- 8*3. $ )))/ ; 5*4(*(( ;,()( ; (( ; 2(()* *) 5)* 2,-),,,( ((),()(+ &,<(*((+ '0*,-,(') -*))*+2,),, )(()(4+)*) ()(,))+ 0(%:?
43 (- 8*3. ),, - )))/ ; ))*)()* ; (*))* ; ))*(((()( ; ()*)()* ; ))* ; 3(4()0)* *) 5)* 0))))*+ ))*,))0+ 2,()()*)() )*)))*,+ 0(@A$# 4-)($; (- 8*3. ) 5)* (- 8*3. 0(@A$# 4-)($;, 8*3./ '*)() (,))* 5))*( ) (,)* 5)* 0($%A$?$> (+#$?;### 4-)($;
44 (- & 8*3. ; '()* ; *())))* ; ))).)))*)* ; ))* 5)* 0($%A$?$> (+#$?;### 4-)(% (- 8*3. *.&&&,* )))/ ;,'B() ; 'B ; ))) ;,'B ; )()'B 5)* (- ((/B))5* &()*5&()*$@@@=$!/?; > &&& 8*3. ; )) ; &)*) ; 1() ; '))(1 ; ))) ; '),)*)) ; &) 5)* 0( #? (+ #:#% (+#@?
45 (- 8*3. & & )))/ ; (,)))* ; ((((())* ; 1(()** *) *) 5)* ())((0* ));)+* )),)+2,0( )4*)))))0 )+2,)***) <+*,))(),<((())( (())),)*)) )+ 0($#$> (+#$#;#$?#% (+#@? (- 8*3. "& )))/ ; )((()(,)C(( ; <)( ; 1)(,) ; 1(*)* *) 5)* ())() (+2,0 )()))(),))+ )(,)+2,) )<))<+ 0($"(($$ 4-)("
46 / (- 8*3. )))/ ; *)(( ; (*)*) ; 1)*))()*) ; &0(15D *) 5)* (),(*)*) )))(*();)(* )+)()(() )(,+ 0(#"(($#$#
47 ! "!# $!" #$%#! &'()*+, ) -&.'/ ( 0/ 1(. $ " + " "" "+ " 23+ 2% 4 5 $45""+5" %3+ " " + % 9!& ' 6<: =%==7 $ $: '+ ; " &+ " (+,+ ()* ; """>" >""$"; ; ;; ;?;@ 5?;; ;?! "#$ * =A$?;; #?" 2
48 +,#-' ".'*' &+,+-. $%6 7 $" 67"+!+$ &+ 5 " " + $%:,.B A2:C/.B /& <2 : DC5 +6&..)76(E7+ :5?"+9C+ A $% "" : '+@F6&..,75 $+56&E7+#$ %:- F9+ &+@F6&..)75 $+""+#$%:- F9 +
49 ! "# $%!" #$%#! &'()*+,'''-&.'/ ( -/ 0(. $ " $ + $ + 1" 2 $ 3 $ 4 2 $ $% % $ +$ $ + 5 +$ "$ $ + # 6 $ $ 7$ 8 "+ + 9" "$ + 9" $:$ % 1'3 95; 1&369; 1(3:%; 1< $%" 1/3: $= >! ":6 + >:%+ >%:+ > &6+ >! $ 6 $ % % + >$+ > 6+?=..@'&=..&=..@-=..@A 1
50 $%1(. 3+7$ $ $ +"B B "$+ C &+ (+ 89B AD6 E A% F+ C )+ D?+ 7%$ '.+ 9 # "$ -..+ & D"9=C'..G $" 9A,'/$%,(. &.'/ ' C H< " $ 5$$ $ """$ +$ 5 $"+ $$ $517$E635 " 5+D "$ +D 5 % :%$I&J IJIJIJIJIJ+D$ $$ + 6= >D+A" =HH+59+HHH5 +1 $ 3 >,+!+" =HH$$$++H K E%=KEB+B$,+ < &..)D+1D#?F)5'5-???<5F&-5?3+ D$6 " 2$= =HH$$$++HL9''H MHBDH5<H 2
51 ( &&-91D3 &) % B!" B D9" /&&7'/)++-5-(' #$%#'..(& 9''*+ 8 E89" B B NE $ N% N! (,'&? 5'& 65 O'<) =HH$$$++HL9''H MHBDH5<H5/H5'<H 6'+ &&-91D3 *+)"* % B!" B D9" /&&7'/)++-5-(' #$%#'..(& 9''*+ 8 E89" B B NP$$ NP$$ % NP$$ $% (,'&'< 5'F 65 O'<) =HH$$$++HL9''H MHBDH5<H5/H5'<H 3
52 , 6&+ &&-91D3 -$ % B!" B D9" /&&7'/)++-5-(' #$%#'..(& 9''*+ 8 E89" B B NP$$ "9 $ N6 ( 7,'(? 5'& 65 ' =HH$$$++HL9''H MHBDH5<H5/H5'-H 6(+ &&-91D3./0 % B!" B D9" /&&7'/)++-5-(' #$%#'..(& 9''*+ 8 E89" B B N$ NP$ $66" ( 7,'('< 5'F 65 & 4
53 =HH$$$++HL9''H MHBDH5<H5/H5'FH 6<+ &&-91D3 ') % B!" B D9" /&&7'/)++-5-(' #$%#'..(& 9''*+ 8 E89" B B NP$ $% (,'<? 5'& 65 =HH$$$++HL9''H MHBDH5<H5/H5')H &&-91D3."2* % B!" B D9" /&&7'/)++-5-(' #$%#'..(& 9''*+ 8 E89" B B N$ %%IJIJ$ NP$ $%"" (,'<'< 5'F 65 ( =HH$$$++HL9''H MHBDH5<H5/H5')H 5
54 3 6/+ &&-91D3 &+ % B!" B D9" /&&7'/)++-5-(' #$%#'..(& 9''*+ 8 E89" B B 4 NP$ $ 62$ NP$ $"$ 55 ( A,'-? 5'& 65 O '& 6F+ &&-91D3 / % B!" B D9" /&&7'/)++-5-(' #$%#'..(& 9''*+ 8 E89" B B C ( B $%"; :$$$;8 D# 8 #8 8##8 AQ;,''? 5'& 6
55 653 B$ = '1%'+-3 <1<+'5<+<<+?5<+'&3 O 6)+ 5 &&-91D % B!" B D9" /&&7'/)++-5-(' #$%#'..(& 9''*+ 8 E89" B B O (8 C; ( B";"+; ED#; $+! $ "H" +,'''< 5'F 65 B$ = <1<+'5<+&3 / 6'+ &&-91D3 $ % B!" B D9" /&&7'/)++-5-(' #$%#'..(& 9''*+ 8 E89" B B $ $ ( A,'-? 5'& 7
56 ! "#"$! % &' "( 6'( 7.47'7'*8!" #$%& "'()*+#!* *,'*(*-*(' *',.*'.',/*0(*' '.**'0(* '((.''*/&-*..-*''0''*,*',/ ''1 '('**'*'2 3..'(*'*'','*,&& (0.4, 3.'(' 3 5.''*'.'((.',. 3.(,'*3.('... 3 &'(('0'((.',' ('''*.((. 3 **..(.*.'., ''0,(**(*.'' *('#/"9*((:0 *('/&416,8/5*.*,0 /*(;<**'0(02 3 =0(=,',$.', 3 -*$'17>&'35(( 3 3'$.14, 3 3%.(5''= 3,*%'$ 3.;':'1 /#9#!*(?1/ #/*(;<**'0(0 3 9' 3 ='$((5> 3 :'>*='$(( 3 $.1' 3 $'', 3 *(!!) /#9#!*(?1 "/*(;<**'0(0 3 ='@.'0% 3 10'0(((<3
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doi: /jech (9*(6!8&,'%*143 C.2$:. &0%%*BBBI!!*($.',>/A/)5@2!/!B#7J740.(9*(6! 8*,(:*'( -*20'. =94?4'L*'<,*'',,M 6! 8# ' $'. / 904%'14<6! 8&@.(&%.%';''4$:.*2%.( '%'9)2A!3AA 9.*(($%*(6! 8'J*<0@ J*N=.*''$:$ 6#8!A3
58 ! "# "$! %& "'( 5?/??6!""#$!%&''()*)+$,-./,.$00+" $$1' 0"230!,"0$) +4& +05)!6 '7 -'-,8#- 9&'4-: :5 '''6;; ' :7 <,9=''' &-5 6 > :: - ' 5620+,'$0*$" 56*0+,'$++0*$@ / A56*40B,'C*$!+0 - & - - & D56*#0),'C*$! D *40!,'C*$!+0 - >E< -,9=
59 :39/*30!,'C*$!+0 "& ) * + :&--' -/< ' 4 - */'4 7/ -D- 4' 4' (& F D*7G H FGH3- F:&-&EGI A= F G=/- F&-A7GI&> FG>->
60 !"!# $ %&!' 91 " :#5:1 :1 ;! "!##!$%&&$ '()*%''" +,-. /0.1%"23-1# 1 " "% " * ' #1 % % 1 1 " "1 #1 #1 #1 1#1 (# & # 1 #( 1 ' 1 4 &"" ( !( (1& 5 # 1 # % #1 " 1# ' 1(16 1" / %11% " 1&1 #1 18 (1 1" 1% # 1" #1 #11 8 # 1 # " #1# 1 5' 04# # 11 11" 1 1 # %# %9 # &1 <1 1" " ;14 1%4 (1(#1< #" # "1' %#.7 6"((4" # 11" 179;# " "#1 19## (1(111 ( # 1;9; "&5 11 "#1 ( 9-;8%727 1" ##1 %& 57" 1"# # #( ( 1 ( ( '< #" &#<8%,727 =((4" # "#1 11 ("# > %72 7 /?8 %" ## " #1"#1 4 1% 1'/ 1% %"1 1#1 " ' 45 1" % # '@45 A?
61 #1 # # 9''4141;#1" #1 8%727A#% 1 " 1 " (" ( # > (## 1 (1(#1 " 8%.727@ /1(!&( )( * + "1(1# 1# # 1(1# 7-BA1 C4 < 7+-BA1 D/ # "(#
62 0 #5 =,-./((-( (0! "!##!$%&&$ '()*%''" A 1 17# 1 "#1 19## (1(111 ( # 1; C &5 11 #1#1 ( ( & 1 1 " 1" 1%" " 1 & 1"" %#"#1 11 ### "! 1 1% & 0 #! & # 1 # & # 1 # & / #1 9-; & "- & ( -1 ( % <9##1 # &1; 11 # 1 ( " <: 11"< 1 " 1, 0 #5 =,-./((-( (0! "!##!$%&&$ '()*%''" 1" ##1 %& 57" 1"# # #( ( 1 ( ( < #" ( & 1 1 " 1" ##1 %& 5
63 & & ## 11 & %#" 1##( & "#( (1 #1 #1 1 & % & # 1 # % 11 # 1 ( " <: 11"< 1" 1 0 #5 = -(- $(($(( $(' /? D1" 1"" '?)# '" =((4" # "#1 11 (" # > 1 ( & 1"" # "#1 1 & 1 1("# "# & 1 (" & 1"" " & 1"" 1" "# & ##% 1 #1 " % <# G11% ( " <1"< 1" 1
64 0 #5 ($$$-$ $( /#% D #'#%)#'" %" ## " #1"#1 4 1% 1' / 1% %"1 1#1 "' 45 1" % # '@45 A?#1 # # 9''4141;#1"#1 ( &(#1& # 195 # &" &(1 9; 1; #1 (1 ' &1 14 "1 (1 #1 1' &<# # 1" &## ' & # " " "" 1% 1 # 1% ' &1 "% " # % ' ' # 1 ( " <1"< 1" (' '$( '1()"# ' ' 1 " 1 " ("( #,' (## 1 (1(#1 "
65 @=* ( & 1 1" ( 1? "1"( & 1 1 1"( & 0 1" <# 1 # "( # & / "# 1" ( "(""%1 1 "# " %1 & 11 " 11 "# 1 & "< #" "# 1 & 1 "(""%""?(1 1% 1 1 & "# 11%(& 1$# # ( & "< #" 1 & # "1( & ("1 # ( & ( " 1 1" # < #1 H,-I' # " ' $ 0#1D%8E7,--&,-+' /1( 'H,--I4## (""%1 %1 ##1 "?(1 1% 1 'D ',--827EJEE' /1( 'H,--FI'1 " / " 1 7 ( 1 % # "" '@=',--F872,E' /1( 'H,--EI1 # ( 1 # # 1 7( " 1 19; '#1 " 272-&2,- 6< 'H,--EI1 1& # "# 1 1 " 1 11 " 1 1# 1.& # # (1 11.&%(11 '87F-&F-E' 2 <#",& 1 ( " <1"< 1" 1
66 Cindy Padilla!" # $% &%% & ' ( ) %% *% % & % % % * % '% * ' % $ * & +%%* ( $ % $ $ %% $ %, * *% % ( -. % % % * % $ % *& % $ * '%, % '( / %% % ' ** %% &2%* (!" 1%+5 %8,882 3 '&%$*4'( / 5 % %% & %%$% / 5 o / & & %6 %% % o / -7 * $ %$( 5 5)% $$ # 59:5 5;$ 7)%$ %$9 %*1-7)2 /< <5559:5 5 "5 %%#% %*1-7)2 3 <5559:5 :5%%'% %*1-7)
67 2(/ : <5559:5 5 %*1-7)2. = <5559:5 # $ # % &%%*$ %*% &( )'%. ;%*7%*%;8 >%%:>; ' &
68 Introduction to health geography Cartographic and GIS tools - graphic semiology,?$a*4' /$?5 %%7+ % * - / *-7) - /& $ $ %$ - / % <?-7)
69 ,?$A*4' /$ Explanatory spatial analysis?5 %%7+ % * =7 *% % 3 B % '% % - /& %% & %%% % - / *% - / % - / %-7)'%6 %% - /& $ %% %%(? -7)& /&%$& 4(
AREAS OF CONCENTRATION
Dr. Shruti Mehta, Director The development of antibiotics, improved access to safe food, clean water, sewage disposal and vaccines has led to dramatic progress in controlling infectious diseases. Despite
More informationClinical trials (1) Bill Friedewald. 12h : Lunch 12h : Lunch 12h : Lunch 12h : Lunch 12h : Lunch 14h
French School of Public Health Ecole des Hautes Etudes en Santé Publique Master of Public Health - Semester 3 Weeks 37 to 41: from Tuesday 8 th September to 6 th October 2009 Module Code 203, Core curriculum,
More informationSPPH Control of Communicable Diseases January - April 2018
SPPH 520 - Control of Communicable Diseases January - April 2018 TIME: LOCATION: INSTRUCTORS: OFFICE: ASSISTANT: Mondays, 9:00AM- 12:00PM Room 143, School of Population and Public Health Bldg Dr. David
More informationPasteur course MODELING OF INFECTIOUS DISEASES
Pasteur course MODELING OF INFECTIOUS DISEASES PROGRAM 2017-2018 Modeling of Infectious Diseases 2017-2018 CO-DIRECTORS OF THE COURSE Pierre -Yves BOËLLE Université Pierre et Marie Curie Hôpital Saint
More informationPublic Health Professor: Dr. Seema Yasmin Course Description Student Learning Objectives/Outcomes Required Textbooks and Materials
Public Health HLTH 4380.001: Special Topics in Healthcare Mondays and Wednesdays 1:00 2:15 p.m., ECSN 2.110 Spring 2015 Professor: Dr. Seema Yasmin Email: sxy143030@utdallas.edu Office: HH 2.132 Phone:
More informationEPI 220: Principles of Infectious Disease Epidemiology UCLA School of Public Health https://ccle.ucla.edu/course/ Syllabus Winter 2016
EPI 220: Principles of Infectious Disease Epidemiology UCLA School of Public Health https://ccle.ucla.edu/course/ Syllabus Winter 2016 Course information Time: Tuesdays and Thursdays 4-5:50 PM Location:
More informationSPPH Control of Communicable Diseases January - April 2016
SPPH 520 - Control of Communicable Diseases January - April 2016 TIME: LOCATION: INSTRUCTORS: OFFICE: ASSISTANT: Mondays, 9:00AM- 12:00PM Room 143, School of Population and Public Health Bldg Dr. David
More informationSyllabus. Mathematical Modeling of Infectious diseases
Syllabus Mathematical Modeling of Infectious diseases - 2009 Credit: 3 credits Faculty: Annelies Van Rie Teaching Assistant for computer practicum: Sarah Radke Time: Spring 2009, Monday, 1 3:50 PM Purpose
More informationA UNIQUE NETWORK OF EXPERTISE DEDICATED TO THE FIGHT AGAINST INFECTIOUS DISEASES
A UNIQUE NETWORK OF EXPERTISE DEDICATED TO THE FIGHT AGAINST INFECTIOUS DISEASES Since 1888, date of its creation, has been committed to contain infectious diseases by working directly in regions where
More informationIntroduction to Infectious Disease Modelling and its Applications
Introduction to Infectious Disease Modelling and its Applications Course Description Intensive course: 19 th 30 th June, 2017 1 Introduction Infectious diseases remain a leading cause of morbidity and
More informationEpidemiology overview
Epidemiology overview Riris Andono Ahmad 1 Public Health Approach Surveillance: What is the problem? Problem Risk Factor Identification: What is the cause? Intervention Evaluation: What works? Implementation:
More informationModule 5: Introduction to Stochastic Epidemic Models with Inference
Module 5: Introduction to Stochastic Epidemic Models with Inference Instructors:, Dept. Mathematics, Stockholm University Ira Longini, Dept. Biostatistics, University of Florida Jonathan Sugimoto, Vaccine
More informationInfectious Disease Epidemiology and Transmission Dynamics. M.bayaty
Infectious Disease Epidemiology and Transmission Dynamics M.bayaty Objectives 1) To understand the major differences between infectious and noninfectious disease epidemiology 2) To learn about the nature
More informationImage of Ebola viruses exiting host cells HUMAN VIRUSES & THE LIMITATION OF ANTIVIRAL DRUG AGENTS
Image of Ebola viruses exiting host cells HUMAN VIRUSES & THE LIMITATION OF ANTIVIRAL DRUG AGENTS APRIL 2017 Infectious viruses are a global health threat Since the approval of the first antiviral drug
More informationChildhood Vaccination and Immunisation
DIRECTORATE GENERAL FOR INTERNAL POLICIES POLICY DEPARTMENT A: ECONOMIC AND SCIENTIFIC POLICY WORKSHOP Childhood Vaccination and Immunisation Brussels, 19 June 2013 MEETING DOCUMENT Policy Department A:
More informationImage of Ebola viruses exiting host cells HUMAN VIRUSES & THE LIMITATION OF ANTIVIRAL DRUG AGENTS
Image of Ebola viruses exiting host cells HUMAN VIRUSES & THE LIMITATION OF ANTIVIRAL DRUG AGENTS MAY 2017 1 Infectious viral pathogens are a significant global health threat to mankind 2 Since the approval
More informationProgram Director. Mission Statement
School of Public Health and Health Services Department of Exercise Science Master of Science in Exercise Science Strength and Conditioning 2011-2012 Program Director Todd A. Miller, PhD Department of Exercise
More informationSPPH Control of Communicable Diseases January - April 2013
The University of British Columbia Centre for Disease Control 2206 East Mall Vancouver, BC V6T 1Z3 Canada MD MHSc FRCPC PH: 604.822.3910 FX: 604.822.4994 david.patrick@ubc.ca DIRECTOR Robert C. Brunham,
More informationDepartment of Epidemiology and Population Health
401 Department of Epidemiology and Population Health Chairperson: Professors: Professor of Public Health Practice: Assistant Professors: Assistant Research Professors: Senior Lecturer: Instructor: Chaaya,
More informationAdjunct Faculty, Division of Epidemiology UC Berkeley School of Public Health. San Francisco Department of Public Health.
Infectious Disease Threats in the 21st Century: Prevention, Control, and Emergency Response Tomás J. Aragón, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division
More informationModule 5: Introduction to Stochastic Epidemic Models with Inference
Module 5: Introduction to Stochastic Epidemic Models with Inference Instructors: Tom Britton, Dept. Mathematics, Stockholm University Ira Longini, Dept. Biostatistics, University of Florida Jonathan Sugimoto,
More informationMODELLING THE SPREAD OF PNEUMONIA IN THE PHILIPPINES USING SUSCEPTIBLE-INFECTED-RECOVERED (SIR) MODEL WITH DEMOGRAPHIC CHANGES
MODELLING THE SPREAD OF PNEUMONIA IN THE PHILIPPINES USING SUSCEPTIBLE-INFECTED-RECOVERED (SIR) MODEL WITH DEMOGRAPHIC CHANGES Bill William M. Soliman 1, Aldous Cesar F. Bueno 2 1, 2 Philippine Science
More informationPHS 801 EPIDEMIOLOGY OF INFECTIOUS DISEASES (3 credits)
PHS 801 EPIDEMIOLOGY OF INFECTIOUS DISEASES (3 credits) COURSE DESCRIPTION and OBJECTIVES This course is designed to provide an introduction to the principles and practice of infectious disease epidemiology.
More informationEnvironmental Health Sciences PhD Curriculum Emory University Matriculation 2017
Read the Laney Graduate degree completion requirements: http://www.gs.emory.edu/academics/completion/index.html Courses in italics: some students may have already had these foundation courses in their
More informationEnvironmental Health Sciences PhD Curriculum Emory University Matriculation 2018
Read the Laney Graduate degree completion requirements: http://www.gs.emory.edu/academics/completion/index.html Students must earn at least 54 credit hours at the 500 level or above to qualify for candidacy.
More informationin control group 7, , , ,
Q1 Rotavirus is a major cause of severe gastroenteritis among young children. Each year, rotavirus causes >500,000 deaths worldwide among infants and very young children, with 90% of these deaths occurring
More informationMISMS: International influenza research activities at the Fogarty International Center, NIH
MISMS: International influenza research activities at the Fogarty International Center, NIH Stacey Knobler and Gerardo Chowell For the Multinational Influenza Seasonal Mortality Study Group (MISMS) Division
More informationProgram Director. Mission Statement
School of Public Health and Health Services Department of Exercise Science Master of Science in Exercise Science Clinical Exercise Physiology 2011-2012 Program Director Dr. Larry Hamm Department of Exercise
More informationEPID Introduction to Public Health Communicable Diseases of Public Health Importance. (pdf version)
EPID 600 - Introduction to Public Health Communicable Diseases of Public Health Importance (pdf version) Concept Control of acute infectious disease is one of the oldest public health practices. It just
More informationEPIDEMIOLOGY (EPI) Kent State University Catalog
Kent State University Catalog 2018-2019 1 EPIDEMIOLOGY (EPI) EPI 50013 CLINICAL EPIDEMIOLOGY BASICS 3 (Cross-listed with PH 40013) The purpose of this course is to develop an understanding of clinical
More informationThe Incidence Decay and Exponential Adjustment (IDEA) model: a new single equation model to describe epidemics and their simultaneous control.
The Incidence Decay and Exponential Adjustment (IDEA) model: a new single equation model to describe epidemics and their simultaneous control. David N. Fisman, MD MPH FRCP(C) Professor, Dalla Lana School
More informationEfficacy of Vaccination against HPV infections to prevent cervical cancer in France
Efficacy of Vaccination against HPV infections to prevent cervical cancer in France Laureen Ribassin-Majed, Catherine Hill, Rachid Lounes To cite this version: Laureen Ribassin-Majed, Catherine Hill, Rachid
More informationTable of Contents. EHS EXERCISE 1: Risk Assessment: A Case Study of an Investigation of a Tuberculosis (TB) Outbreak in a Health Care Setting
Instructions: Use this document to search by topic (e.g., exploratory data analysis or study design), by discipline (e.g., environmental health sciences or health policy and management) or by specific
More informationSteady Ready Go! teady Ready Go. Every day, young people aged years become infected with. Preventing HIV/AIDS in young people
teady Ready Go y Ready Preventing HIV/AIDS in young people Go Steady Ready Go! Evidence from developing countries on what works A summary of the WHO Technical Report Series No 938 Every day, 5 000 young
More informationPUBHLT2015 Public Health Biology. Introduction. Class Meeting Times. Course Goals. Syllabus for Fall semester 2013 (University term 2141)
Syllabus for Fall semester 2013 (University term 2141) Introduction This course introduces students to a variety of different biological concepts important to Public Health. It is intended to give students
More informationThe Syndemics of HIV, Hepatitis, and Overdose
The Syndemics of HIV, Hepatitis, and Overdose Sara Zeigler Associate Director for Policy Office of Policy, Planning and Partnerships (proposed) Centers for Disease Control and Prevention National Center
More informationThe mathematics of diseases
1997 2004, Millennium Mathematics Project, University of Cambridge. Permission is granted to print and copy this page on paper for non commercial use. For other uses, including electronic redistribution,
More informationRunning head: INFLUENZA VIRUS SEASON PREPAREDNESS AND RESPONSE 1
Running head: INFLUENZA VIRUS SEASON PREPAREDNESS AND RESPONSE 1 Electron micrograph of H1N1 Virus (CDC, 2009) Influenza Virus Season Preparedness and Response Patricia Bolivar Walden University Epidemiology
More informationSchool of Health Sciences PBHE 605 Quarantine 3 Credit Hours Length of Course: 8 weeks Prerequisite: None
School of Health Sciences PBHE 605 Quarantine 3 Credit Hours Length of Course: 8 weeks Prerequisite: None Instructor Information Please refer to the Syllabus tab for your instructor s contact information
More informationConfronting infectious diseases and the role of vaccination: A global perspective KATE ANTEYI. MD, MPH, MBA
Confronting infectious diseases and the role of vaccination: A global perspective KATE ANTEYI. MD, MPH, MBA Technical Advisor, United States Agency for International Development (USAID) Chair, WONCA Working
More informationEconomics of Vaccine Development A Vaccine Manufacturer s Perspective
Economics of Vaccine Development A Vaccine Manufacturer s Perspective Gerald Voss The Value of Vaccines 2 29 diseases are currently preventable by vaccination Global public health Cervical cancer 1 Diphtheria
More informationIS39 CP6108 [1]
112 9 26 2017 40 2018:28:112-118 (human papillomavirus, HPV) DNA 100 16 18 31 33 35 39 45 51 52 56 58 59 68 6 11 26 40 42 53 54 55 61 62 64 66 67 69 70 71 72 73 81 82 83 84 IS39 CP6108 ( ) [1] 2012 588,000
More informationModelling screening of HPV vaccinated birth cohorts. The infection transmission system
Modelling screening of HPV vaccinated birth cohorts Dr. Iacopo Baussano Imperial College, London & UPO/CPO-Piemonte, Italy. The infection transmission system Infectious Agent in case of CC: men in case
More informationTable S1- PRISMA 2009 Checklist
Table S1- PRISMA 2009 Checklist Section/topic TITLE # Checklist item Title 1 Identify the report as a systematic review, meta-analysis, or both. 1 ABSTRACT Structured summary 2 Provide a structured summary
More informationDeterministic Compartmental Models of Disease
Math 191T, Spring 2019 1 2 3 The SI Model The SIS Model The SIR Model 4 5 Basics Definition An infection is an invasion of one organism by a smaller organism (the infecting organism). Our focus is on microparasites:
More informationCenters for Disease Control and Prevention (CDC) FY 2009 Budget Request Summary
Centers for Disease Control and Prevention (CDC) FY 2009 Budget Request Summary The President s FY 2009 Budget Request for the Centers for Disease Control and Prevention (CDC) discretionary funding is
More informationSuggested Exercises and Projects 395
Suggested Exercises and Projects 395 Projects These suggested projects are taken in part from the recent book A Course in Mathematical Biology: Quantitative Modeling with Mathematical and Computational
More informationMEETING OF INTERESTED PARTIES
WORLD HEALTH ORGANIZATION MEETING OF INTERESTED PARTIES GENEVA, 3 TO 7 NOVEMBER 2003 Timetable and annotated agenda Please note that the timetable is indicative and that the timing of discussions may vary
More informationOur next questions are about Contingency Management.
II.B.04.01 01 Our next questions are about Contingenc t. Higgins and Petr (1999) describe Contingenc t as the sstematic reinforcement of desired behaviors and the withholding of reinforcement or punishment
More informationHuman Biology: Immunology and Public Health. level 6 (3 SCQF credit points)
Human Biology: Immunology and Public Health SCQF: level 6 (3 SCQF credit points) Unit code: H4LB 76 Unit outline The general aim of this Unit is to develop skills of scientific inquiry, investigation and
More informationSyllabus. The University of Florida College of Pharmacy's Pharmacist Immunization Program contains the following modules:
Syllabus PHARMACIST IMMUNIZATION PROGRAM UNIVERSITY OF FLORIDA COLLEGE OF PHARMACY The University of Florida is accredited by the Accreditation Council for Pharmacy Education as a provider of continuing
More informationDr. Th. Leventouri. 777 Glades Road Boca Raton, FL Tel: Fax:
Dr. Th. Leventouri Professor of Physics Director, Medical Physics Program Department of Physics Director, Center for Biomedical and Materials Physics Charles E. Schmidt College of Science 777 Glades Road
More informationInfectious Diseases-HAI Idaho Department of Health and Welfare, Division of Public Health Boise, Idaho. Assignment Description
Infectious Diseases-HAI Idaho Department of Health and Welfare, Division of Public Health Boise, Idaho Assignment Description The Fellow s assignments will primarily focus on projects within the HAI and
More informationHPV Epidemiology and Natural History
HPV Epidemiology and Natural History Rachel Winer, PhD, MPH Associate Professor Department of Epidemiology University of Washington School of Public Health rlw@uw.edu Human Papillomavirus (HPV) DNA virus
More informationESTIMATION OF THE REPRODUCTION NUMBER OF THE NOVEL INFLUENZA A, H1N1 IN MALAYSIA
ESTIMATION OF THE REPRODUCTION NUMBER OF THE NOVEL INFLUENZA A, H1N1 IN MALAYSIA Radzuan Razali * and SamsulAriffin Abdul Karim Fundamental and Applied Sciences Department, UniversitiTeknologiPetronas,
More informationIHI Biomedical Sciences Group. Joseph Mugasa, PhD, PD. Stakeholders Meeting
IHI Biomedical Sciences Group Joseph Mugasa, PhD, PD Stakeholders Meeting Jan 2013 Overview Biomedical group carries out a range of laboratory studies with the aim of understanding the pathogenesis, diagnosis
More information8/10/2015. Introduction: HIV. Introduction: Medical geography
Introduction: HIV Incorporating spatial variability to generate sub-national estimates of HIV prevalence in SSA Diego Cuadros PhD Laith Abu-Raddad PhD Sub-Saharan Africa (SSA) has by far the largest HIV
More informationDisability-Adjusted Life Year conversion
Disability-Adjusted Life Year conversion CASE STUDY #1: HIV CASES TO DALYS Joanna Emerson, MPH, David Kim, PhD AIM This study aims to convert disease-specific health outcomes (e.g., HIV cases) reported
More informationMaintaining a Safe and Adequate Blood Supply in the Event of Pandemic Influenza. Guidelines for National Blood Transfusion Services
Maintaining a Safe and Adequate Blood Supply in the Event of Pandemic Influenza Guidelines for National Blood Transfusion Services 19 May 2006 1 Rationale Current global concern that an occurrence of pandemic
More informationContents. Mathematical Epidemiology 1 F. Brauer, P. van den Driessche and J. Wu, editors. Part I Introduction and General Framework
Mathematical Epidemiology 1 F. Brauer, P. van den Driessche and J. Wu, editors Part I Introduction and General Framework 1 A Light Introduction to Modelling Recurrent Epidemics.. 3 David J.D. Earn 1.1
More informationActivities in 2010, Priorities for 2011
European Centre for Disease Prevention and Control Activities in 2010, Priorities for 2011 Presentation to ENVI Committee by Marc Sprenger, Director ECDC 27 October 2010 Part 1: Examples of ECDC s work
More informationTransmission of DS-TB and MDR-TB. C. Robert Horsburgh, Jr. Boston University School of Public Health
Transmission of DS-TB and MDR-TB C. Robert Horsburgh, Jr. Boston University School of Public Health Outline Epidemiologic factors in transmission Ability of the transmitter to transmit Susceptibility of
More informationCourse Curriculum for Master Degree in Medical Laboratory Sciences / Diagnostic Molecular Biology and Human Genetics
Course Curriculum for Master Degree in Medical Laboratory Sciences / Diagnostic Molecular Biology and Human Genetics The Master Degree in Medical Laboratory Sciences / Diagnostic Molecular Biology & Human
More informationDr Suresh Kumar Consultant Infectious Diseases Physician Hospital Sungai Buloh. Influenza Vaccination of Health Care Workers-
Dr Kumar Consultant Infectious Diseases Physician Hospital Sungai Buloh Influenza Vaccination of Health Care Workers- Outline Influenza in the tropics Rationale and purpose of HCW vaccination Efficacy
More informationIMPACT OF HPV IMMUNIZATION STRATEGIES & POTENTIAL FOR CERVICAL CANCER ELIMINATION
IMPACT OF HPV IMMUNIZATION STRATEGIES & POTENTIAL FOR CERVICAL CANCER ELIMINATION Marc Brisson Full Professor Université Laval, Canada SAGE meeting October 24, 2018 Geneva 1 Questions A. What is the potential
More informationVaccine Efficacy, Effectiveness and Impact. G. HANQUET, KCE, 9 September 2017
Vaccine Efficacy, Effectiveness and Impact G. HANQUET, KCE, 9 September 2017 RvB - CA, 16/09/2014 Outline The confusion Vaccine effects Methodologies Challenges Implications for decision making 2 Life
More informationMICROBIOLOGY II MICR 401
MICROBIOLOGY II MICR 401 Course Description Microbiology II is an organ/system approach to infectious diseases. The course begins with a brief description of the major signs and symptoms of infectious
More informationAging and Cancer in HIV
Aging and Cancer in HIV Ronald Mitsuyasu, MD Professor of Medicine Director, UCLA Center for Clinical AIDS Research and Education Group Chairman, AIDS Malignancy Consortium (AMC) Age distribution of HIV-infected
More informationDEPARTMENT OF EPIDEMIOLOGY 2. BASIC CONCEPTS
DEPARTMENT OF EPIDEMIOLOGY EXIT COMPETENCIES FOR MPH GRADUATES IN GENERAL EPIDEMIOLOGY 1. DEFINITION AND HISTORICAL PERSPECTIVES 1. Historical Trends in the most common causes of death in the United States.
More informationDisease and immunity Faculty of Engineering, Science and Built Environment become what you want to be
Module guide Disease and immunity Unit Ref. SBS - 2-511 Blackboard site Faculty of Engineering, Science and Built Environment 2015/16 Level 5 become what you want to be 1 Table of contents 1.0 UNIT DETAILS...
More informationA Brief History. A Brief History (cont.) February 1, Infectious Disease epidemiology BMTRY 713 (Lecture 7) mathematical Modeling for ID
Infectious Disease Epidemiology BMTRY 713 (A. Selassie, DrPH) Lecture 7 Mathematical Modeling: The Dynamics of Infection Learning Objectives 1. Define what models mean 2. Identify key concepts in ID mathematical
More informationMalaria in pregnancy programmes: challenges and priorities in antimalarial drug development for African pregnant women
7 th MIM Pan African Malaria Conference 15-20 April 2018 Dakar, Senegal The power of sharing science EDCTP session on Malaria in pregnancy programmes: challenges and priorities in antimalarial drug development
More informationCalifornia s Experiences Using Tuberculosis Whole Genome Sequencing
California s Experiences Using Tuberculosis Whole Genome Sequencing Martin Cilnis MS, MPH Epidemiologist California Department of Public Health, TB Control Branch, Outbreak Prevention and Control Section
More informationCANCER AND VIRUSES OVERVIEW 3 CURRICULUM LINKS AND AIMS 4 BACKGROUND INFORMATION FOR TEACHERS 5 ACTIVITIES 7 STUDENT WORKSHEETS 10
OVERVIEW 3 CURRICULUM LINKS AND AIMS 4 BACKGROUND INFORMATION FOR TEACHERS 5 ACTIVITIES 7 STUDENT WORKSHEETS 10 OVERVIEW This lesson will introduce the topic of vaccination, using the cervical cancer vaccine
More informationAdvanced Lecture on One Health
The 6th International Symposium Advanced Lecture on One Health 13:30~16:30 Sept 2, 2013 Lecture Hall, Graduate School of Veterinary Medicine, Hokkaido University, JAPAN Program 13:30~14:30 Dr. Ruben Donis
More informationGovernment of Canada Federal AIDS Initiative Milestones
HIV in Canada: Trends and Issues for Advancing Prevention, Care, Treatment and Support Through Knowledge Exchange Michael R Smith, Senior Policy Advisor, Programs and Coordination Division, Centre for
More informationChampioning the Fight Against Cervical Cancer in the Developing World
Championing the Fight Against Cervical Cancer in the Developing World Investing in Women and Girls: Funding Opportunities for Cervical Cancer Dr. Viviana Mangiaterra Session code: SP1-2 Track Disclosure
More informationHealth care workers and infectious diseases
Introduction Health care workers and infectious diseases Objectives 1. What is an infectious disease?? 2. What is an infection and disease?? 3. Causes of re-emerging of the problem of the infectious diseases
More informationStochastic Elements in Models to Support Disease Control Policy How Much Detail is Enough?
Stochastic Elements in Models to Support Disease Control Policy How Much Detail is Enough? MARGARET BRANDEAU Department of Management Science & Engineering Department of Medicine Stanford University Agenda
More informationLahey Clinic Internal Medicine Residency Program: Curriculum for Infectious Disease
Lahey Clinic Internal Medicine Residency Program: Curriculum for Infectious Disease Faculty representative: Eva Piessens, MD, MPH Resident representative: Karen Ganz, MD Revision date: February 1, 2006
More informationDetailed Parameters of the BARDA Interactive Flu Model
Detailed Parameters of the BARDA Interactive Flu Model Regional Vaccine Distribution Rates for Influenza No data were available to quantify the typical and maximum possible flu vaccination rates in either
More informationCalifornia s Experiences Using Tuberculosis Whole Genome Sequencing
California s Experiences Using Tuberculosis Whole Genome Sequencing Martin Cilnis MS, MPH Epidemiologist California Department of Public Health, TB Control Branch, Outbreak Prevention and Control Section
More informationManagement of Antiretroviral Treatment (ART) and Long-Term Adherence to ART
Thailand s Annual International Training Course (AITC) 2017 Management of Antiretroviral Treatment (ART) and Long-Term Adherence to ART I. Proposal Title: Management of Antiretroviral Treatment (ART) and
More informationPandemic Risk Modeling
Pandemic Risk Modeling Ghalid Bagus,, FSA MAAA CFA Financial Risk Management June 5, 2008 2008 Milliman, Inc. The material and content contained in this presentation are the proprietary information of
More information1:15 2:00 KEYNOTE ADDRESS:
GHDx Course 1 Point-of-Care Diagnostics for Global Health July 13 July 17, 2009 University of Washington, Seattle, WA http://www.path.org/dxcenter/ Day 1 Monday (July 13 th, 2009) 8:30 8:45 Outline of
More informationModelling HIV prevention: strengths and limitations of different modelling approaches
Modelling HIV prevention: strengths and limitations of different modelling approaches Leigh Johnson Centre for Infectious Disease Epidemiology and Research Background Models of HIV differ greatly in their
More informationAgent-Based Models. Maksudul Alam, Wei Wang
Agent-Based Models Maksudul Alam, Wei Wang Outline Literature Review about Agent-Based model Modeling disease outbreaks in realistic urban social Networks EpiSimdemics: an Efficient Algorithm for Simulating
More informationMathematics of Infectious Diseases
Mathematics of Infectious Diseases Zhisheng Shuai Department of Mathematics University of Central Florida Orlando, Florida, USA shuai@ucf.edu Zhisheng Shuai (U Central Florida) Mathematics of Infectious
More informationPublic Health Resources: Core Capacities to Address the Threat of Communicable Diseases
Public Health Resources: Core Capacities to Address the Threat of Communicable Diseases Anne M Johnson Professor of Infectious Disease Epidemiology Ljubljana, 30 th Nov 2018 Drivers of infection transmission
More informationFORECASTING IN COMMUNICABLE DISEASES
WORLD HEALTH ORGANIZA IIDN I... I ome. III'... EIII.r. M R.. lllrrl ORGANISATION MONDIALE DE LA SANTE a.rlll rhlllli ~.Ia M'~ltlrrl"'II'I.. tll. REGIONAL COMMITTEE FOR THE EASTERN MEDITERRANEAN Forty-sixth
More informationInfectious Disease Epidemiology BMTRY 713 January 11, 2016 Lectures 2 Continuation of Introduction & Overview
Infectious Disease Epidemiology BMTRY 713 Lectures 2 Continuation of Introduction & Overview Learning Objectives 1. Explain the magnitude of infectious diseases 2. Describe major principles in infectious
More informationThe new German strategy on HIV, Hepatitis B, C and STI, an integrated approach. Ines Perea Ministry of Health, Germany
The new German strategy on HIV, Hepatitis B, C and STI, an integrated approach Ines Perea Ministry of Health, Germany Reasons for a new strategy in 2016 New international agreements (SDG s) Renewed political
More informationVaccine Preventable Disease Alameda County
Vaccine Preventable Disease Alameda County Erica Pan, MD, MPH, FAAP Deputy Health Officer Director, Division of Communicable Disease Control and Prevention Alameda County Public Health Department Clinical
More informationI mun u i n s i atio i n o n u p u d p a d te
Immunisation update Brian Eley Paediatric Infectious Diseases Unit Red Cross War Memorial Children s Hospital Department of Paediatrics and Child Health University of Cape Town Immunisation schedules,
More informationOutline. Introduction to Epidemiology. Epidemiology. Epidemiology. History of epidemiology
Outline Introduction to Epidemiology Joshua Vest Epidemiologist Austin/Travis County Health & Human Services Department Define History Basis of epidemiology Objectives of epidemiology Causal inference
More informationHPV Transmission. Rachel Winer, PhD, MPH Department of Epidemiology University of Washington
HPV Transmission Rachel Winer, PhD, MPH Department of Epidemiology University of Washington rlw@u.washington.edu Disclosure Information I have no financial relationships to disclose. Human Papillomavirus
More informationPRIMARY IMMUNODEFICIENCY DISEASES 3RD EDITION FREE
page 1 / 5 page 2 / 5 primary immunodeficiency diseases 3rd pdf Primary Immunodeficiency Diseases presents discussions of gene identification, mutation detection, and clinical and research applications
More informationPARALLEL SESSION 2.4
PARALLEL SESSION 2.4 CHANGING DYNAMICS: EMERGING INFECTIOUS DISEASES AND ANTIMICROBIAL RESISTANCE IN AN ERA OF EXPANDING GLOBAL HUMAN POPULATION GROWTH AND MOVEMENT BACKGROUND The global human population
More information