Global and Regional Burden and Trands

Global and Regional Burden and Trands - Based on surveys of the prevalence of infection and of disease, on assessments of the performance of surveillance systems and on death registrations, there were an estimated 9.2 million new cases of TB in 2006, of which 4.1 million were smear-positive. The WHO African region had the highest estimated incidence rate (363 per 100,000 population), but the majority of TB patients live in the most populous countries of Asia. Five countries – Bangladesh, China, India, Indonesia, and Pakistan – have almost half the world’s population (46%) and produced about half (48%) of all new TB cases arising worldwide in 2006. Illustrates the global distribution of new TB cases in 2006, in terms of numbers and rates per 100,000 population.

Estimated of new cases of Tuberculosis 1997

map the spread of Tuberculosis

Much of the work of the WHO and partners focuses on the 22 countries known as the high-burden countries (HBCs). These are the countries which, in 2002, were estimated to have had the highest numbers of incident TB cases in the year 2000: Afghanistan, Bangladesh, Brazil, Cambodia, China, the Democratic Republic of the Congo, Ethiopia, India, Indonesia, Kenya, Mozambique, Myanmar, Nigeria, Pakistan, Philippines, the Russian Federation, South Africa, Thailand, Uganda, the United Republic of Tanzania, Viet Nam and Zimbabwe. Changes in estimates due to new data or techniques, and likely changes in incidence rates and population sizes, mean that this list no longer exactly matches the list of the 22 countries with the largest number of new cases each year, but it is still true that, between them, the HBCs account for 80% of new TB cases arising annually. shows the estimated incidence and prevalence of TB and mortality from TB for 2006. Globally an estimated 1.7 million people died from TB in 2006, 231,000 of them infected with HIV.

Estimates of TB incidence, prevalence and mortality are uncertain, and rely to varying degrees on assumptions about the quality of surveillance data, about the quality and impact of treatment and about the duration of disease and case-fatality rates. New methods for evaluating the burden of TB and impact of control are needed. In our view these should be based principally on assessments of the quality of surveillance systems, backed by data obtained from surveys of the prevalence of disease. These methods and the resulting data would help to meet increasing demands from donor agencies (such as the Global Fund to Fight AIDS, Tuberculosis, and Malaria) to demonstrate the impact of the activities which they fund, and of international experts to increase the transparency surrounding statistics provided through databases such as those of the WHO  A recently established task force on measurement of TB will guide work on improving estimates of the burden of TB and the impact of control.

Estimates of the incidence of multidrug-resistant TB (MDR-TB; caused by strains of M. tuberculosis resistant to at least isoniazid and rifampicin) are even more uncertain than those of overall TB incidence. Drug susceptibility testing is not widely available, although WHO guidelines for incorporating the diagnosis and treatment of drug-resistant TB into the routine activities of national TB control programmes are likely to lead to improved information about the proportion of TB cases which are MDR. Current estimates (based on multivariate analysis) are that 489,000 cases of MDR-TB arose in 2006 among new and previously treated TB cases.

Extensively drug-resistant TB (XDR-TB) is defined as TB due to bacilli resistant to any fluoroquinolone, and at least one of three injectable second-line drugs (capreomycin, kanamycin, and amikacin), in addition to isoniazid and rifampicin. The magnitude of the XDR-TB problem globally is not yet known. Where the transmission of M. tuberculosis has been stable oincreasing for many years, the incidence rate is relatively high among infants and young adults, and most cases are due to recent infection or reinfection. As transmission falls, the caseload shifts to older adults, and a higher proportion of cases comes from the reactivation of latent infection. Therefore, in the countries of Western Europe and North America that now have low incidence rates, indigenous TB patients tend to be elderly, while patients who are immigrants from highincidence countries tend to be young adults.

Allowing for the difficultiesof diagnosing childhood TB, estimation exercises indicate that there are relatively few cases among 0–14 year olds; while this age group accounts for nearly 30% of the world’s population, it accounts for only 12% of estimated cases. In 2006, countries reported 1.6 million smear-positive TB cases among men, but only 884,000 among women. In some instanceswomen have poorer access to diagnostic facilities, but the broader pattern also reflects real epidemiological differences between the sexes: while there is some evidence that young adult women (15–44 years) are more likely than men to develop active TB following infection, this effect is typically outweighed by the much higher exposure and infection rates among adult men

Tuberculosis Control

Tuberculosis Control - The path of TB epidemics is clearly determined not only by the biological and social phenomena discussed above under Risk Factors, but also by explicit efforts to control the disease. Prior to the development of antibiotic therapy for TB, the main methods of control available were reducing transmission by isolating infectious patients, and increasing the likelihood of spontaneous recovery by providing patients with rest and improved nutrition. Both these aims were achieved by treating TB patients in sanatoria, where case-fatality rates were about 50%.

providing patients with rest 

improved nutrition

Modern TB control is based on early detection and treatment, particularly of infectious cases. Treatment is generally effective; the average global cure rate was 84.7% for smear-positive cases treated in 2005 by programmes following international recommendations.Treatment has, therefore, a direct impact on the prevalence of disease and on mortality. Furthermore, transmission is reduced, as infectious cases quickly become non-infectious once treatment is started. In addition to the primary goal of TB control (early diagnosis and treatment), national TB programmes or health authorities can (and, to varying degrees, do) influence the flow of individuals along the paths shown in in the following ways: by implementing appropriate ‘infection control’ strategies (ensuring adequate ventilation in healthcare centres, minimizing contact between infectious and susceptible individuals in order to reduce transmission; by providing preventive treatment (isoniazid preventive therapy, IPT) to infected individuals who do not have TB disease (thus returning them from the latently infected pool to the pool of susceptibles); by collaborating with national acquired immunodeficiency syndrome (AIDS) programmes to identify and provide appropriate care for HIV-infected TB patients; and by providing nutritional support to TB patients and their families, thus improving their nutritional status and perhaps increasing the likelihood of recovery for patients, decreasing the likelihood of infection for family members and encouraging patients to complete treatment.

Finally, roughly 100 million infants (>80% of the annual cohort) are vaccinated each year with Bacillus Calmette- Gue´rin (BCG), the effect of which is mainly to prevent serious forms of disease in children: meningitis and miliary TB. The potential of existing and possibly future tools for reducing the burden of TB, particularly with reference to international targets, is discussed further below.

Transmision, Infection,Disease

Transmision, Infection,Disease - Tuberculosis is a rare disease, whose prevalence is measured or estimated in cases per 100,000 population. TB is also a slow-moving disease – the time scale of epidemics is decades rather than weeks or years. The natural history of TB helps us understand the driving forces behind these ‘slow epidemics of a rare disease’,1 and the temporal and geographical patterns in its distribution. In Fig. 3.1, arrows represent the processes by which individuals enter and leave each of the states represented by the boxes. An individual can be uninfected, latently infected, or can have primary or post-primarydisease.

Pulmonary tuberculosis

Tuberculosis

Infection with Mycobacterium tuberculosis, the causative agent of TB, results from inhaling droplets containing the bacilli, which are produced when a person with infectious TB coughs, talks, or sneezes (see Chapter 14 for a more detailed discussion). A widely used rule of thumb in TB epidemiology is that each untreated, infectious TB case infects, on average, about another 10 individuals each year.2,3 

The estimated prevalence of smearpositive disease was just under 0.1% (90 per 100,000) in 2005,4 which corresponds to an annual risk of infection of just under 1%. A recent assessment of new infections caused by all infectious TB cases (treated and untreated) suggests an average of six new infections per case, which would imply an even lower annual risk of infection.5 Of infected individuals, only about 5% (in the absence of other predisposing conditions) develop ‘progressive primary’ disease following infection.6 Progression is typically slow, with time to development

of primary disease averaging 3–4 years.

For the remainder, who enter the pool of ‘latently infected’ individuals, there is a low annual risk of developing TB by ‘reactivation’ of infection. Whether latent bacteria remain viable for the full lifespan of all infected people is unknown, but the risk of reactivation certainly persists into old age for many. Infection is associated with only partial immune protection from reinfection.7–9 Thus, particularly in areas where infection transmission is high, infected persons remain at risk of disease resulting from reinfection. At the population level, the relative importance of primary disease, of post-primary disease resulting from reactivation and of post-primary disease following reinfection varies according to past and current patterns of transmission and breakdown to disease. 

The majority of individuals infected with M. tuberculosis (but not with HIV) do not develop TB disease; the lifetime risk of pulmonary disease among infected individuals has been estimated at 12% for England and Wales in the second half of the twentieth century.8 It is this large pool of infected, healthy individuals and the typically long interval from acquiring infection to developing disease which give the slow-moving epidemics of TB their momentum, and mean that they generally respond slowly to control efforts.

While the low rate of infection and breakdown to disease make TB a relatively rare disease, it is principally the high case-fatality rate which makes it one of major public health significance. Left untreated, and in the absence of HIV, about two-thirds of smearpositive cases will die, mostly within 2 years.3 For untreated smear-negative cases, case fatality rates are lower: 10–15%.10,11 Even on treatment, over 10% of smear-positive patients die in settings where adherence to treatment is low, or rates of HIV infection or drug resistance are high, although in other settings as few as 2% of smear-positive patients die while on treatment.

Risk Factors

Risk Factors - The rates at which individuals move along the various arrows from one box to another in determine the burden and distribution of disease. Factors which affect those rates, or which affect the proportion of individuals who take each path when an arrow branches, will in turn affect the size and dynamics of the epidemic. These ‘risk factors’ result from inherent characteristics of the biology of the human host and of the mycobacterial pathogen and from characteristics of the environment. Some key risk factors and their effects are shown in . 

such as crowded living conditions

malnutrition

While the association between certain risk factors and TB disease is clear, it is in practice difficult to determine which part of the life cycle of TB is affected by a particular risk factor (e.g. whether it is the risk of infection or the risk of breakdown to disease which is affected). The problem of confounding further complicates the study of risk factors; factors such as crowded living conditions, malnutrition, and exposure to indoor air pollution from cooking fires are clearly all linked to poverty, and difficult to study independently.

The likelihood of transmission depends largely on the proximity and duration of contact with an infectious TB case, and is therefore increased by poorly ventilated, overcrowded housing. People in close contact with infectious cases (family members, health workers, prisoners) are at elevated risk of infection. Susceptibility to tuberculosis may be affected by factors such as tobacco smoking, silicosis, exposure to smoke from cooking fires and excessive alcohol use as well as by HIV infection, but it is difficult in practice to distinguish between the effect of such factors on susceptibility to infection and the likelihood of progression to disease.

Malnutrition influences breakdown to disease,although to what extent requires careful investigation in order to distinguish pre-existing malnutrition from wasting resulting from TB. Nutrition is also to influence the likelihood of recovery from disease. HIV infection has a dramatic effect on the likelihood of breakdown to disease, increasing the likelihood of breakdown from a lifetime risk of between 10% and 20% to an annual risk of over 10%.

Both age and sex have biological and social effects which are difficult to distinguish. The risk of developing primary disease is lower in children than in adults, and children are more likely to develop severe forms of disease in organs other than the lungs (e.g. tuberculous meningitis). Young women (15–44 years) may be more likely than men to develop active TB following infection, but the socially driven effects of gender are generally more marked than the biological effects of sex. Men and women experience different environmental risk factors, and demonstrate different health-seeking behaviours and tendencies to adhere to treatment

Mathematical Modelling Of M. Tuberculosis Transmission

Mathematical Modelling Of M. Tuberculosis Transmission - With few exceptions, every case of TB results from the airborne transport of MTB from an infectious source to a vulnerable host. Primarily an intracellular pathogen, MTB is adapted to replicate extracellularly in necrotic lung cavities, to endure the rigors of aerosolization in mucus as tiny respiratory droplets, to survive the process of rapid drying into droplet nuclei, and to remain infectious after airborne transport through a variety of harsh environments. Potentially lethal environmental exposures include the extremes of air temperature and humidity, ambient levels of air pollution, and natural ozone and irradiation (Fig. 2.2). 

Tuberculosis Transmission

Dots in air represent droplet nuclei containing M. Tuberculosis

Little is known about these adaptive processes, but the selective pressure is strong since only adapted strains can propagate. Finally, organisms surviving the gauntlet of airborne transmission face innate and adaptive host defences honed, in some human populations, by generations of natural selection. Virulence, the ability of the pathogen to overcome host defences and cause infection, is also selected for by the necessity of transmission. Microbes, of course, adapt much faster than can humans, even to the antimicrobials invented to tilt the contest in our favour. The mathematical modelling that follows attempts to quantify the relationship between the infectious doses generated by the source case(s) and the number of infected humans, but ignores the fact that most tubercle bacilli released from the source case are unlikely to cause infection due to factors cited earlier. In addition, probability plays a role in whether a vulnerable host inhales an infectious dose of MTB.

In an attempt to characterize the transmission process as a probability that a vulnerable host will acquire TB infection, Wells and Riley (Richard’s brother, Edward, an engineer) developed a mathematical model that expands upon and modifies the Soper mass balance equation for epidemiological investigations, incorporating the following operational assumptions:

1. steady-state conditions in which the infectious source is

constant;

2. complete air mixing within a defined volume or space being

studied;

3. equal susceptibility among exposed individuals to infection;

4. Poisson’s law of small chances which employs the natural

logarithm e;

5. uniform virulence of organisms released into the air space; and

6. random distribution of infectious particles within a defined

space.

This model states that for a single generation of infection:

C ¼ Sð1 e

Iqpt=QÞ;

where:

C ¼ number of new cases,

S ¼ number of susceptibles exposed,

e ¼ natural logarithm,

I ¼ number of infectious sources,

q ¼ number of quanta (infectious doses) generated per unit time

in minutes,

p ¼ human ventilation rate in L/minute,

t ¼ exposure duration, and

Q ¼ infection-free ventilation in the room in L/second.

Although this model applies to situations that meet the assumptions above (i.e. a single room or enclosed space with a defined ventilation), it can be applied, although with less validity, to spaces served by a single central ventilation system (i.e.HVACsystem) andwhose air spaces are connected – an essential component for infections which are airborne. The larger the space being considered, the less evenly distributed (mixed) airborne particles may be, thus also potentially reducing the validity of this model for that air space. Despite these limitations, the model has been useful in examining the relative importance of transmission factors in real-life exposure situations. In epidemiological investigations of epidemics in which C, S, I, p, t, and Q were known or estimated, values for q could be calculated as a representation of the infectiousness of the index source case. This was done for a few scenarios of TB transmission: the patients on Riley’s TB ward in the 1950 experiment with guinea pigs, an office outbreak, and a bronchoscopy case on a patient with TB in an intensive care unit (Table 2.2). What follows is a discussion of how the Wells–Riley equation has been used to compare the intensity of exposure to TB and how it can inform approaches to reducing transmission. In the first situation, Riley’s TB patients were receiving TB drug treatment and the infectiousness values represent that of the entire six-bed ward. In the second scenario, a 30-year-old woman returned

towork in a welfare office for an additionalmonth before shewas diagnosed with cavitary, sputumsmear-positive TB, atwhich time contact with fellow employees ended.85 Of 67 co-workers who were initially tuberculin skin test negative, 27 (40%) had conversions to positive upon repeat testing 3 months later. One non-infectious secondary case resulted in a worker who had declined treatment of latent infection.

The office building had been the subject of repeated air quality complaints, and several air quality assessments had been done before and after the TB exposure. A mathematical analysis of the exposure was prompted by the suspicion of several workers that inadequate ventilation was responsible for the large number of infected workers. All values of the Wells–Riley equation were known or estimable except q, the number of infectious quanta generated by the source case.

By calculation, the source generated 13 infectious quanta per hour.

Further calculations showed that outdoor air ventilation at the low end for acceptable air quality (15 cubic feet perminute (cfm) per occupant, based on average roomCO2 values of 1000 ppm) contributed to transmission. However, the model was useful also for indicating that doubling the ventilation would reduce the risk of infection by approximately half (Fig. 2.3). Thirteen workers would still have been infected, according to the model. Moreover, an additional doubling of ventilation, to 60 cfm per occupant, would again reduce the risk by half, leaving approximately six workers unprotected. Both the potential of a moderately infectious patient to infect many contacts over a prolonged period of time and the limitations of building ventilation to prevent transmission were demonstrated, within the assumptions and limitations of the modelFor the third scenario, 

Catanzaro applied the Wells–Riley equation to an episode of transmission in an intensive care unit where an unsuspected patient, initially smear negative for TB, underwent intubation and bronchoscopy. During the 2½ hours of the procedures, 10 of 13 susceptible room occupants became infected. By calculation, the source produced a remarkable 250 infectious quanta per hour. However, the ventilation rate in the intensive care unit was extremely low, and further calculations predicted substantial improvements by increases in ventilation that were

Human Host Factors Which Affect Vulnerability to Tuberculosis Infection

Human Host Factors Which Affect Vulnerability to Tuberculosis Infection - Once the TB bacillus finds an entry into the human lung, its interaction with the host immune system and the impact of the host’s other comorbid medical conditions ultimately determines whether infection is established and whether it progresses to clinical disease. Substantial immunological research has begun to elucidate key steps in the human immune system’s attempt to contain and eliminate TB. Simply stated, once MTB breaches the structural defences of the upper airways and reaches the distal lung, innate mechanismsinvolving macrophages are the first defence against infection, followed by the acquired CMI and DTH, which together usually contain further spread of infection within the host.

Factors Which Affect Vulnerability to Tuberculosis Infection 

Tuberculosis

Defects in any portion along this elaborate and still incompletely understood defence pathway could render a host more vulnerable to MTB infection, thereby enhancing transmission. Compared with what is known about the immune defences operative during active TB, relatively little is known about the immune response that contains latent MTB infection. Similarly, the events that trigger reactivation of latent MTB infection are poorly understood. CD4 T cells certainly have an important role in this process, since numerous studies document the higher rates of reactivation in HIV-infected individuals. There is debate, however, about whether HIV infection increases the risk of acquiring TB infection in the first place since this appears to be predominantly determined by macrophage function.

Exposure to both silica dust and silicosis increases the rate of reactivation TB.76–78 Inhaled silica particles damage alveolar macrophage cell membranes, the same cells which MTB typically encounters upon inhalation and deposition in the distal lung. Allison and Hart79 showed that sublethal doses of silica enhanced the growth of MTB in macrophage cultures, and guinea pig exposure studies revealed that inhalation of quartz (a chief component of silica dust) reactivated TB lesions that were healing.80 Still other studies suggest that humoral and cell-mediated immunity may also be altered in silica exposure.81 One would expect silica exposure to enhance MTB transmission as well as disease progression.

It is known from human postmortem studies in which single isolated tubercles are found in the lungs that even a single inhaled droplet nucleus is sufficient in some individuals to initiate MTB infection. Yet as seen by TST or interferon gamma release assay (IGRA) results, not all exposed individuals acquire TB infection, even after comparable types of exposures. Observations like these underscore the variability in human susceptibility to TB, which is generally attributed to differences in immune function, genetics, and concomitant health conditions that predispose to infection and disease.

Epidemiological studies by Stead and colleagues 82,83 specifically suggest an enhanced risk of MTB infection, but not disease reactivation, associated with ethnic or racial background. The authors maintained that these factors were surrogates for the historical selection of populations with innate MTB resistance resulting from the evolutionary pressure of the several hundred-year-old TB epidemic in Europe and North America. Persons in central Africa, Aboriginals, and others isolated from this epidemic pressure remained vulnerable because there was no such selection.82,83 It has long been an accepted tenet of medicine that, once infected with MTB, the latent infection is lifelong, with a small but persistent risk of reactivation to active disease. Occasional observations of skin test reversions in the absence of anergy, with or without treatment, had been dismissed as the exceptions to the rule. 

However, these observations are now supported by reversions in IGRA results. The possibility that transient MTB infection may be part of the pathogenesis of the disease has several implications for transmission. First, skin test surveys may greatly underestimate transmission in populations since infected persons may have already reverted their skin test or IGRA back to negative by the time they were tested. Second, if infection can be transient, progression to disease may depend on reinfection to a degree not previously suspected. Indeed there is evidence that what appears to be high rates of reactivation TB disease among recent arrivals to the United States from high-prevalence areas may in fact represent recent infection or reinfection.84 Finally, if natural MTB infection is often transient, and reinfection is important to pathogenesis, then perhaps vaccines may not be as beneficial as hoped.

Mycobacterial Factors, Strain Differences, and Interactions with Sources, Environment, and Host

Mycobacterial Factors, Strain Differences, and Interactions with Sources, Environment, and Host - As mycobacteria multiply during the course of infection, they acquire point mutations, frame shift mutations, deletions, and genetic sequence insertions as a result of chance DNA transcriptional errors and recombinations. As discussed earlier, there may be as many as 108 or 109 organisms within a lung cavity, and, within this population, genetic mutations may occur at a rate of 1 in 10 7 to 1 in 10 10 per bacterium per generation.60 These genetic mutations can be associated with a variety of phenotypic outcomes, including alterations in drug resistance, nutrient uptake, metabolism, or interaction with host immune cells, that is, altered virulence.

Mycobacterium Tuberculosis and the desease tuberculosis

Multidrug resistant Mycobacterium tuberculosis

How often do these mutations result in reduced mycobacterial fitness, how often do compensatory mutations occur that restore fitness to the wild-type state, and how important are these microbial determinants of infection or disease amid the many other factors depicted in Fig. 2.2? These are among the most important questions being addressed by molecular epidemiological and laboratory researchers.

Anecdotal observations, combined with molecular typing data, suggest that some strains propagate more readily or are more ‘fit’ than others. In the natural history of TB infection, there are several stages that might be altered by genetic mutations that could influence the propagation of TB, In 1998, Valway et al.61 reported on the results of a contact investigation in the setting of an unusual outbreak of TB. Interestingly, while the rate of skin test conversion was unusually high and the reactions unusually large among exposed individuals, the rate of disease development was lower than expected, suggesting that this strain of TB was highly infectious, a strong stimulator of DTH, but not particularly virulent. Conversely, the strong induced host response itself might explain the lower rate of disease progression.

Several decades earlier, Middlebrook and Cohn62 described transmission patterns for isoniazid (INH) susceptible and resistant strains of MTB among guinea pigs exposed via the aerosol route. INH resistant strains were less virulent for the guinea pigs than the susceptible strains, as evidenced by smaller and less numerous foci of infection on autopsy, fewer organs involved, a milder clinical course, and prolonged survival. Early on, researchers attributed the loss of virulence of INH resistant strains to a loss of catalase activity, the enzyme responsible for metabolizing INH from a prodrug to its metabolically active form.63–65 Subsequent work has found associations between the type of KatG mutation responsible for catalase activity and the apparent virulence of the organism. 

As an example, it was shown that, although both point mutations and deletions in the gene sequence disrupt the production of catalase, the deletions confer a more profound reduction in catalase levels, a higher degree of resistance to INH, and a more marked attenuation in virulence than point mutations.66 In contrast to these observations for INH mutations, mutations which lead to pyrazinamide resistance alone tend not to alter the fitness of MTB.67 Whether mutations which contribute to drug resistance necessarily reduce the reproductive fitness of the MTB has recently been the subject of considerable debate.

Ordway et al.68 examined 15 different clinical isolates of MTB, some of which were fully drug sensitive, INH resistant, or multidrug resistant. They found that, although growth rates in experimentally infected mice varied for each of the 15 isolates, these growth rates did not correlate with the extent of drug sensitivity or resistance.68 Likewise, Cohen and colleagues69 recently evaluated epidemiological data available on transmission of MDR-TB using mathematical models to determine whether drug resistance mutations also result in a loss of reproductive fitness. In their analysis they conclude that the fitness of drug-resistant strains is quite heterogeneous and that attempting to discover an average degree of reproductive fitness for MDR-TB upon which to base programmatic and policy decisions may be misleading.69 Instead, they argue, it is important to determine the distribution of highly resistant and less resistant strains, so that outbreaks can be averted and handled appropriately. 

As a real-life example of this heterogeneity, we might consider another contact investigation conducted by Texeira et al.70 in Brazil, who evaluated rates of TST conversion among household contacts of index cases of MDR-TB. They found no association between the degree of drug resistance and rates of TST conversion or disease development among the household contacts, even though the drug-resistant index cases were infectious for a longer period of time than the drug-sensitive cases in their study. Using IS6100 pattern molecular typing techniques, they also confirmed that the secondary cases of TB among household contacts were from the same strain as the index case

for any given household, thereby eliminating any doubt that secondary cases in a household were from a non-household exposure.70

As discussed elsewhere in this volume, developments in the molecular biology and genetics of MTB have permitted closer analysis of the interplay of genes, proteins, and bacterial enzymes in the life cycle of this organism. We mention this here only in relation to transmission. Mycobacterial growth in the face of exogenous stressors has been shown to be dependent upon the elaboration of gene products called sigma factors, which regulate defence regulons within the mycobacterial genome. aboratory studies in which several sigma factors were mutated demonstrated that mutation of the sigma factors had no impact on the ability of the H37Rv strain of mycobacterium to grow in culture dishes or within in vitro macrophage systems, but had a substantial impact on the in vivo growth and replication of H37Rv within a guinea pig infection model. Among the factors studied, mutations in SigC affected the adaptive survival of H37Rv in guinea pigs more than mutations in SigF.