Infectious Diseases Sapience

Transcription

1 Infectious Diseases Sapience Anton Stoltz BSc, BSc (hons), MSc, MBChB, Mmed(Int), PhD, Infectious Diseases Subspecialist HOD: Division of Infectious Diseases Department of Internal medicine University of Pretoria University of Pretoria

2 It took all of history up until 1830 to put 1 billion people on the planet By 1930, 100 years later, there were 2 billion people on the planet By 1974, 44 years later, there were 3 billion people on the planet By 1986, 12 years later, there were 4 billion people on the planet 7.6 billion people June 2018

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5 Tree of Life Health Immunity Sleep Appetite Memory Personality ttps://

6 It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one that is most adaptable to change? Charles Darwin: Origin of Species

7 7 TED talks

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9 Drivers of Infectious Diseases Microbial adaption and change Human susceptibility to infection Disease source Climate and weather/changing ecosystems Human demographics and behavior Economic development and land use/poverty Technology and industry Breakdown of public health measures Disease outcomes War and famine Lack of political will Adapted from Foresight. Infectious Diseases: preparing for the future. OFFICE OF SCIENCE AND INNOVATION. UK

10 Aeroplanes in 24h period versus infection outbreaks Human demographics and behavior International travel and commerce Nature, Vol February 2008 doi: /nature06536

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12 Welcome to Sott.net, Wed, 09 May 2018 THE WORLD FOR PEOPLE WHO THINK

13 Tuberculosis: Do we have a problem?

14 Airborne Particles Sneezing Coughing Talking

15 Particle size and settling velocity Diameter (µm) Terminal settling velocity (m/s) Time to fall 1 meter Distance to touchdown (m) E hours E minutes E minutes E seconds E seconds Expelled large droplets were carried: More than 6 m away by exhaled air at a velocity of 50 m/s (sneezing) 2 m away at a velocity of 10 m/s coughing) Less than 1 m away at a velocity of 1 m/s (breathing). Data by Paul Jensen, CDC, personal communication X. Xie et al, How far droplets can move in indoor environments revisiting the Wells evaporation falling curve,. Indoor Air 2007; 17:

16 Droplets becoming airborne particles Josserand C, Lemoyne L, Troeger R, Zaleski S Droplet impact on a dry surface: triggering the splash with a small obstacle. J. Fluid Mech. 524:47 56 Annu. Rev. Fluid Mech : Downloaded from

17 Wells evapo atio -falling curve Evaporation time, falling time and escape time of droplets of varying diameter (Tp0 ¼ 33 C, T ¼ 20 C, RH ¼ 50%, U0 ¼ 10 m/s. X. Xie et al, How far droplets can move in indoor environments revisiting the Wells evaporation falling curve,. Indoor Air 2007; 17: Wells, W.F. (1934) On air-borne infection.study II. Droplets and droplet nuclei, Am. J. Hyg., 20,

18 Particle size and disease transmission Aspects of pulmonary drug delivery strategies for infections in cystic fibrosis - where do we stand? Expert Opinion on Drug Delivery Feb 2:-24 January 2015

19 Airborne infections Roy CJ, Milton DK. Airborne transmission of communicable infection the elusive pathway. N Engl J Med 2004;350(17):

20 Factors affecting disease transmission via aerosolized modes Type of respiratory activity Frequency of respiratory activity Number of particles generated Site of infection Pathogen load Pathogen type Gralton J, et al. The role of particle size in aerosolised pathogen transmission A review, Journal of infection, (2011), 62, 1-13 Relative humidity and evaporation Aggregation Mucus properties

21 Aerosol production and suppression DDT Volume 11, Number 1/2 January 2006 Edwards, D.A. et al. (2004) Inhaling to mitigate exhaled bioaerosols. Proc. Natl. Acad. Sci. U. S. A. 101,

22 (CASS) Cough aerosol sampling Photo A C Stoltz

23 Summary of the differentially expressed MDR tuberculosis RNA transcripts between Aerosol and Sputum There are strong indications that aerosol is not simply a sample of sputum Human cough aerosol captured and RNA preserved within seconds has permitted a glimpse at gene expression changes associated with a tuberculosis phenotype free of culture artifacts. Tuberculosis present in aerosol shows significantly different gene expression from those in contemporaneously sampled sputum and different still from cultures from the same patient. This has implications for understanding the basics of transmission, vaccine development, and response to treatment. First Gene Expression Signatures of Captured, Uncultured M. tuberculosis from Human Source Aerosol, Edward A Nardell 1, Caroline M Williams 2, Andrew J Bell 2, Lesibana Malinga 3, Mohammadali R Yavari 2, Amin Bakir 2, Natalie J Garton 2, Anton Stoltz 3, Elsabe DeKock 3 ; Simon Waddell 4, Jay Hinton 5, Kevin Fennelly 6, and Michael R Barer 2, Unpublished 1

24 Tuberculosis present in aerosol shows significantly different gene expression from those in contemporaneously sampled Of 111 RNA Transcript reads: 52 were up and 59 down regulated in aerosol versus sputum 95 transcripts represented protein encoding Compared to aerobic growth in vitro, DosR was significantly upregulated in both sputum and aerosol, and Mce2R genes were significantly up in aerosol vs sputum First Gene Expression Signatures of Captured, Uncultured M. tuberculosis from Human Source Aerosol, Edward A Nardell 1, Caroline M Williams 2, Andrew J Bell 2, Lesibana Malinga 3, Mohammadali R Yavari 2, Amin Bakir 2, Natalie J Garton 2, Anton Stoltz 3, Elsabe DeKock 3 ; Simon Waddell 4, Jay Hinton 5, Kevin Fennelly 6, and Michael R Barer 2, Unpublished data. 1

25 1 Distinct microbiomes detected in Sputum versus Aerosol 16S reads mapped to the ribosomal database. Only exact matches included The role of the lung microbiome in TB disease and effect on the formation of aerosols??? First Gene Expression Signatures of Captured, Uncultured M. tuberculosis from Human Source Aerosol, Edward A Nardell 1, Caroline M Williams 2, Andrew J Bell 2, Lesibana Malinga 3, Mohammadali R Yavari 2, Amin Bakir 2, Natalie J Garton 2, Anton Stoltz 3, Elsabe DeKock 3 ; Simon Waddell 4, Jay Hinton 5, Kevin Fennelly 6, and Michael R Barer 2, Unpublished data.

26 Future of tuberculosis sampling? PLOS One, August 2014 Volume 9 Issue 8 e Sampling Time: 15 minutes Sensitivity: surpassing sputum in newest data Currently 5 different experiment ongoing

27 Mathematical model of airborne infections C =S(1 e Ipt[Q] ) Wells-Riley equation Probability of Infection = s/c S/C =(1 e Iqpt[q/Q] ) C = number of new cases S = number of susceptible individuals exposed e = base of natural logarithms I = number of infectors p = pulmonary ventilation rate of susceptible individuals (0.6 m 3 /h) t = exposure time (hours) Q = absolute room ventilation (m 3 /h) = [q/q] q = u e of i fe tious ua ta p odu ed pe hou y i fe to s Q = volume of disinfected air into which quanta are distributed Riley RL, Mills C, Nyka W. Aerial dissemination of tuberculosis a two year study of contagion on a tuberculosis ward. Am J Hyg 1959; 70: ( ep i ted as lassi A J Epidemiol 1995; 142:3-14)

28 Movement of aerosols in controlled environments? 1 ACH = 63% particles removed Photo and figure, AC Stoltz

29 Consultants/Engineers to Air facility Toby van Reenen - CSIR Prof Paul Jensen - CDC Consultants veterinarians to Air facility Dr Jackey Hooton Dr Dries Kruger Quality control: RETRASOL Regulatory and legal aid at AIR Me Elsabe de kock Figure by A C Stoltz

30 (AIR) Airborne Research Facility Photo: Property AIR facility, University of Pretoria

31 Natural MDR tuberculosis infection from human to guinea pig (Dunkin-Hartley) Intervention room 90 Control room 90 Induration exceeding 6 mm After h PPD Control: Positive control: 5 BCG vaccinated guinea pigs Negative control: 5 PBS injected guinea pigs

32 Institutional Tuberculosis Transmission Controlled Trial of Upper Room Ultraviolet Air Disinfection: A Basis for New Dosing Guidelines Maisie Mphaphlele 1, Ashwin S. Dharmadhikari 2, Paul A. Jensen 3, Stephen N. Rudnick 4, Tobias H. van Reenen 5, Marcello A. Pagano 6, Wilhelm Leuschner 7, Tim A. Sears 8, Sonya P. Milonova 4, Martie van der Walt 9, Anton C. Stoltz 10,Karin Weyer 11, and Edward A. Nardell 2 12 Am J Respir Crit Care Med, Vol 192, Iss 4, pp , August 15, 2015 Kill zone Validation: Spatial Distribution of Fluence Rate from Upper Room Ultraviolet Germicidal Irradiation: Experimental Validation of a Computer-Aided Design Tool. HVAC&R Research. 2012; 18(4): Rudnick SN, First MW, Sears T, Vincent RL, Brickner PW, Ngai P, Zhang J, Levin RE, Chin K, Rahn RO, Miller SL, Nardell EA.

33 Results of AIR GUV experiments Intervention Control UV1 TST TST TST TST Total 0 9 Intervention UV2 TST TST TST Total *p< Control Hazard of becoming infected Combined hazard ratio 4.9 (CI.95: 2.8, 8.6) Efficacy: 84%

34 Surgical Face Masks reduces TB 69/90 control guinea pigs (76.6%; 95% CI) 36/90 intervention guinea pigs (40%; 95% CI) 56% (95% CI, %) decreased risk of TB transmission when patients used masks. Clean Air Solutions. [n.d.]. Infection Transfer Airborne Droplet nuclei. [Online]. Available: info/articles/article.cfm/articleid/4e5f1627-6e B464B55332F68ECC/Page/1. [Accessed 4 January 2016]

35 Portable Room Air Cleaner The selected room air cleaners provided an effective clean air delivery rate equivalent to 11.8 air changes per hour( ACH ) in this application. 25/90 ( 27.75, 95% C.I : 18.5%-37%) infections in the control group. 20/90 ( 22.2%, 95% C.I : 13.6%-30.8 %) infections in the intervention group. A 20% risk reduction of infection observed in the intervention group was not statistically significant. Unpublished data: Nardell E., Jensen P., Stoltz A et al.

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37 Take home message The fast changing world drives infectious diseases (mistakes from the past) Our microbiome is our best ally Airborne infections are complex and difficult to contain Look back to move forward

38 Collaborators Edward Nardell Paul Jensen Matsie Mphaplehle Michael Barer Caroline Williams Elsabe de Kock Tobias van Reenen Ashwin S. Dharmadhikari

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