MAJOR ARTICLE
The Importance of Recent Infection
with Mycobacterium tuberculosis in an Area
with High HIV Prevalence: A Long-Term Molecular
Epidemiological Study in Northern Malawi
Judith R. Glynn,1 Amelia C. Crampin,1,3 Malcolm D. Yates,2 Hamidou Traore,1 Frank D. Mwaungulu,3
Bagrey M. Ngwira,3 Richard Ndlovu,3 Francis Drobniewski,2 and Paul E. M. Fine1
1
Department of Infectious Diseases, London School of Hygiene and Tropical Medicine, and 2Health Protection Agency National Mycobacterium
Reference Laboratory, Kings College Hospital (Dulwich), London, United Kingdom; 3Karonga Prevention Study, Chilumba, Malawi
Background. The proportion of cases of tuberculosis due to recent infection can be estimated in long-term
population-based studies using molecular techniques. Here, we present what is, to our knowledge, the first such
study in an area with high human immunodeficiency virus (HIV) prevalence.
Methods. All patients with tuberculosis in Karonga District, Malawi, were interviewed. Isolates were genotyped
using restriction-fragment–length polymorphism (RFLP) patterns. Strains were considered to be “clustered” if at
least 1 other patient had an isolate with an identical pattern.
Results. RFLP results were available from 83% of culture-positive patients from late 1995 to early 2003. When
strains with !5 bands were excluded, 72% (682/948) were clustered. Maximum clustering was reached using a 4year window, with an estimated two-thirds of cases due to recent transmission. The proportion clustered decreased
with age and varied by area of residence. In older adults, clustering was less common in men and more common
in patients who were HIV positive (adjusted odds ratio, 5.1 [95% confidence interval, 2.1–12.6]).
Conclusions. The proportion clustered found in the present study was among the highest in the world,
suggesting high rates of recent transmission. The association with HIV infection in older adults may suggest that
HIV has a greater impact on disease caused by recent transmission than on that caused by reactivation.
DNA fingerprinting of Mycobacterium tuberculosis has
been used in conjunction with conventional epidemiological approaches to elucidate transmission patterns
in different settings. M. tuberculosis strains with identical DNA fingerprints are said to be “clustered,” and
the proportion of clustering in a population is thought
Received 16 November 2004; accepted 2 March 2005; electronically published
23 June 2005.
Financial support: Until 1996, the Karonga Prevention Study was funded primarily
by LEPRA (The British Leprosy Relief Association) and ILEP (The International
Federation of Anti-Leprosy Organizations), with contributions from the World Health
Organisation/United Nations Development Programme/World Bank Special Programme for Research and Training in Tropical Diseases. Since 1996, the Wellcome
Trust has been the principal funder. J.R.G. was supported in part by the UK Department for International Development and is now funded by the UK Department of Health (Public Health Career Scientist award).
Potential conflicts of interest: none reported.
Reprints or correspondence: Dr. Judith Glynn, Infectious Disease Epidemiology
Unit, London School of Hygiene and Tropical Medicine, Keppel St., London WC1E
7HT, United Kingdom ([email protected]).
The Journal of Infectious Diseases 2005; 192:480–7
2005 by the Infectious Diseases Society of America. All rights reserved.
0022-1899/2005/19203-0016$15.00
480 • JID 2005:192 (1 August) • Glynn et al.
to reflect the amount of recent transmission [1–4]. Using this argument, researchers have estimated the proportion of tuberculosis attributable to recent transmission [1] and how it changes over time [5], as well as
factors associated with clustering and, hence, with recent transmission [1, 6].
Most information has been gained from studies that
attempt to include all tuberculosis cases in a defined
population over several years. Including all cases is important, since incomplete sampling will lead to a failure
to identify clusters and, therefore, to an underestimation of clustering and of the importance of recent transmission [7]. Short studies will also miss clusters [4].
Several population-based studies spanning several years
now exist [5, 8–11], but none have been conducted in
a general population setting in an area of Africa with
a high HIV burden. As part of the Karonga Prevention
Study in northern Malawi, where the HIV infection
prevalence in adults is currently ∼13% [12], we have
had the opportunity to conduct the first long-term pop-
ulation-based molecular epidemiological study of tuberculosis
in an area with a high prevalence of HIV infection.
PATIENTS AND METHODS
In Karonga District, Malawi, suspected tuberculosis cases were
identified in clinics and the district hospital by screening patients who had had a cough for at least 3 weeks and by examining patients with enlarged lymph nodes. Sputum samples
were taken, and, since 1997, aspiration and culture of lymph
nodes has been performed. Tuberculosis treatment is in accordance with Malawi National TB Control Programme guidelines. Patients with tuberculosis were tested for HIV, after
counseling and if consent was obtained [13, 14]. Permission
for the study was received from the Malawi National Health
Sciences Research Committee and from the ethics committee
of the London School of Hygiene and Tropical Medicine.
Sputum smear microscopy and bacteriological culture on Lowenstein-Jensen medium were performed in the project laboratory.
Cultures that morphologically resembled M. tuberculosis were
sent to the Health Protection Agency National Mycobacterium
Reference Laboratory in London, England, for species identification and drug sensitivity testing. All cultures from patients with
tuberculosis in Karonga District since late 1995 have been stored
for DNA fingerprinting. Since 1997, all patients with tuberculosis
have been interviewed and asked about their area of residence
during the previous 5 years for any period ⭓3 months, as well
as about known tuberculosis contacts.
Isolates cultured from specimens collected between late 1995
and early 2003 were included in this analysis. Specimens were
fingerprinted using standard methods based on restriction-fragment–length polymorphism (RFLP) patterns of IS6110 [15]. They
were compared using computer-assisted (GelCompar version
4.1; Applied Maths) visual comparison. The possibility of laboratory error was considered when identical fingerprints were
obtained from specimens from different patients processed on
the same day [14]. These specimens were excluded if there was
no other laboratory evidence of tuberculosis (isolated positive
cultures), if they were the only 2 examples of this RFLP pattern,
or if the patients had other isolates with different patterns.
Some patients had 11 specimen available. To define whether
an RFLP pattern was unique or clustered, patients were included only once unless they had 11 fingerprint pattern (after
likely errors were excluded). Strains were classified as clustered
if at least 2 patients had identical RFLP patterns. This was defined both overall and by time period. After clustering was
defined, patients were only included once, for their first episode
of illness for which an RFLP result was available within the
time period of the study.
Recent transmission was estimated using the “n ⫺ 1” method
[1] ([number of patients in clusters ⫺ number of clusters]/
total number of patients), to allow for an index case in each
cluster. Because of the long duration of the study, this statistic
was reestimated to investigate clustering within given time periods. Each patient was considered to have a clustered strain
in a given time period if another patient had previously had
the same strain within that time period. This “retrospective”
proportion clustered is equivalent to the n ⫺ 1 estimate for that
period (since the first patient with the strain in any cluster is
not clustered).
Risk factors for clustering were examined using overall and
retrospective clustering in different time periods. If 1 index case
per cluster is assumed, then the larger the cluster, the higher
the proportion of patients with recently acquired tuberculosis.
Analyses of risk factors for clustering were therefore repeated
after smaller clusters (2–4 patients and 2–9 patients) were excluded, to approximate an analysis of risk factors for recent
transmission.
RESULTS
Over the period of the study, 1194 specimens from 1044 patients (84% of 1248 culture-positive patients seen during this
period) were fingerprinted. The remaining isolates were contaminated, not viable, or missing. Twenty-five fingerprints were
likely to have been laboratory errors and were excluded. After
multiple isolates per person were excluded, there were 1029
patients with 406 different RFLP patterns. All but 73 had pulmonary tuberculosis. The number of bands in the strains from
all 1029 patients is shown in figure 1.
The proportion clustered was 73.6% (757/1029) overall, or
71.9% (682/948) after the 81 isolates with !5 bands on the
RFLP pattern were excluded. When 1 case per cluster was assumed to be an index case, the proportion of cases apparently
Figure 1. No. of bands in the restriction-fragment–length polymorphism patterns of Mycobacterium tuberculosis strains from 1029 patients
in northern Malawi.
Molecular Epidemiological Study of Tuberculosis in Malawi • JID 2005:192 (1 August) • 481
due to recent transmission was 60.8% by use of the n ⫺ 1
formula, or 59.4% after isolates with !5 bands were excluded.
Clustering was also examined as clustering with isolates obtained previously, using different time windows. The results for
patients with at least 5 bands are summarized in figure 2. The
overall proportion clustered with any previous isolates is equivalent to the cumulative n ⫺ 1 estimate. It increased with time,
as expected, as the data set grew, but reached a plateau after
3–4 years. The other lines in figure 2 show the proportion
clustered with previous isolates within a given number of years.
This proportion increased as the time window lengthened, but
the results for the 4- and 5-year time windows were similar to
each other and to the overall estimate. Of the total retrospective
clustering detected using a 4-year window (recorded from 2000
onward, to ensure that all patients had 4 years of previous data
available), 72% was detected using a 1-year window, 88% using
a 2-year window, and 96% using a 3-year window. For any
given window, the proportion clustered was stable over the
period of the study.
The plateau in the proportion clustered can also be seen by
examining the proportion of new strains (unique or the first
in a cluster) in each year. This fell sharply, from 70% in 1996
to ∼30% each year since 1999. Of the new strains from 1999
on, 17% went on to form clusters.
The cluster size distribution is shown in figure 3. The largest
cluster contained 37 patients, and 24 contained at least 10 patients. Risk factors for clustering were examined using both
overall clustering and retrospective clustering for different time
periods. To avoid incomplete time periods, for retrospective
clustering with a 3-year window, data from 1999 onward were
used; for a 1-year window, data from 1997 onward were used.
Analyses were performed both including and excluding isolates
with !5 bands. The results were similar; results from analyses
excluding isolates with !5 bands are presented in table 1.
The proportion clustered decreased with age, from 175%
among young adults to !60% among patients 155 years of age,
and this decrease was statistically significant (P p .001 , test for
trend). The decrease was more marked for men than women
(P p .1, test for interaction). Women were more likely than men
to have clustered strains. This association persisted after age was
adjusted for but was stronger among older adults. The proportion
clustered was higher among patients who were HIV positive.
Again, this was apparent only among the older adults (P p
.001, test for interaction). The decrease in clustering with age
was seen only among HIV-negative patients: 77% (106/138) of
those !45 years of age were clustered, compared with 53% (35/
66) of those ⭓45 years of age (P p .001). Among HIV-positive
patients, the proportion clustered increased slightly with age: 75%
(238/317) of those !45 years of age, compared with 82% (50/
61) of those ⭓45 years of age (P p .2).
The proportion clustered varied in different areas of the
482 • JID 2005:192 (1 August) • Glynn et al.
Figure 2. Proportion of Mycobacterium tuberculosis strains that clustered with previous isolates. Isolates with restriction-fragment–length
polymorphism patterns with !5 bands were excluded. The gray line shows
the cumulative proportion overall; the other lines show the results when
fixed time windows were used.
district, being lower in the far north and far south of the district
than in the central areas. There was lower clustering among
patients who had lived outside the district during the past 5
years. There was no association with any of the other factors
studied: site of tuberculosis, previous tuberculosis, known family or other contacts with tuberculosis, or drug resistance.
Because of the interactions with age, the multivariate analysis
was conducted for 2 different age groups (table 2). Age 45 years
was used as a cutoff, since the proportion clustered appeared
to decrease after this age. Among patients !45 years of age, the
only factors significantly associated with clustering were area
of residence at the onset of illness and during the previous 5
years. There was a weak association with sex and no association
with HIV-infection status. Among patients ⭓45 years of age,
clustering was more common in women and in patients who
were HIV positive. Clustering was uncommon in patients living
outside the district, but there was no other association with
area of residence or any of the other factors.
When the retrospective clustering approach was used, the
results were similar. There were significant interactions (P p
.001–.009) between age and HIV-infection status and between
age and sex when both the 3-year and 1-year windows were
used. When the 1-year window (after 1996) was used, the only
significant risk factors for clustering in patients !45 years of
age were area of residence and previous tuberculosis, with lower
clustering in those with previous tuberculosis (odds ratio [OR],
0.34 [95% confidence interval {CI}, 0.17–0.68], after adjusting
for area). For patients ⭓45 years of age, the effects of HIVinfection status and sex were similar to those seen with overall
Figure 3.
Cluster size distribution. Patients with unique Mycobacterium tuberculosis strains are not shown.
clustering, and there was more clustering in patients with previous tuberculosis (OR, 2.2 [95% CI, 0.87–5.6], after adjusting
for HIV-infection status and sex). When the 3-year window
(after 1998) was used, only area of residence was a significant
risk factor for clustering in patients !45 years of age, and only
HIV-infection status and sex were significant risk factors in patients ⭓45 years of age, with ORs similar to those found using
overall clustering.
Risk factors for clustering were also examined after smaller
clusters (2–4 patients and 2–9 patients) were excluded. The results were very similar to those overall; associations were found
with area of current and previous residence and with age group,
and associations with HIV-infection status and sex were found
only in patients 145 years of age.
DISCUSSION
In this rural African population, the proportion of strains that
were clustered was among the highest recorded in the world.
Clustering is related to the proportion of tuberculosis due to
recent transmission, and, as expected, the proportion clustered
found in our study was much higher than that found in large
studies in low-incidence settings in the West [1, 2, 8, 16]. The
proportion clustered was similar to that found in 2 very high–
incidence settings in South Africa. In a 6-year study in Cape
Town, the clustering proportion was 72%, and the n ⫺ 1 clustering proportion was 58% [11]; in a 1-year study in the South
African gold mines, the clustering proportion was 50% [17].
This is, at first, surprising, given that the annual risk of infection
with M. tuberculosis in Cape Town is estimated to be 3.5%,
compared with 1% in Karonga District [18]. However, it has
been shown theoretically that, when the annual risk of infection
is constant over time, the clustering proportion will be high:
∼75% for a wide range of infection risks [19].
Measured clustering depends on several factors, including
completeness of sampling, immigration, and time period [4]. In
the present study, 84% of culture-positive patients were included.
Although this is relatively high, some tuberculosis cases will have
remained undiagnosed, as in all populations, and the true proportion clustered is likely to have been even higher. The case
detection rate is not known, but the screening at peripheral clinics
and ongoing case-control studies involving household visits in
the district should have increased it. The extent of the underestimation of clustering is limited by the large cluster sizes, since
strains in large clusters are likely to be recognized as clustered,
even if some patients in the cluster are missed [7].
Our study included a complete district. This will have maximized the chance of observing transmissions occurring within
the study area and, therefore, of recognizing clusters. The district has a population of ∼220,000 and measures ∼150 ⫻ 20
km. It is bounded to the east by Lake Malawi and to the west
by the sparsely populated Nyika Plateau, so population movement occurs only to the north (into Tanzania) and south. The
proportion clustered was lower in the far north and especially
low in the south, suggesting that more transmissions may be
missed in those border areas. The district is largely rural, and
the majority of the population are subsistence farmers, so little
migration might be expected; it is notable, however, that more
than one-third of the patients with tuberculosis had lived outside the district during the previous 5 years for periods of ⭓3
months and that this was associated with reduced clustering,
indicating importation of infections that occurred elsewhere.
A high proportion of clustered cases could also reflect few
introductions of M. tuberculosis into the population in the past
and, hence, a lack of diversity of strains. This has been suggested as an explanation for high clustering in Greenland [9]. Karonga District had been quite isolated in the past, before the
Molecular Epidemiological Study of Tuberculosis in Malawi • JID 2005:192 (1 August) • 483
Table 1.
Risk factors for clustering in patients with tuberculosis.
Clustered: total
Group
No./total (%)
All
Sex
Female
Male
Age group
!15 years
15–24 years
25–34 years
35–44 years
45–54 years
⭓55 years
Area of residence
South
Central rural
Periurban
Urban
North
Far north
Outside district
Lived outside district during past 5 years
No
Yes, in Malawi
Yes, outside Malawi
HIV-infection status
Negative
Positive
Previous tuberculosis
No
Yes
Household/family member with tuberculosis
No
Yes
Other tuberculosis contacts during past 5 years
No
Yes
Tuberculosis type
Smear positive
Smear negative
Extrapulmonary
Drug resistance
None
Isoniazid only
At least 2 drugs
NOTE.
a
P
682/948 (71.9)
Clustered: 3-year time
window, after 1998
Clustered: 1-year time
window, after 1996
No./total (%)
No./total (%)
334/523 (63.9)
.001
386/505 (76.4)
296/443 (66.8)
.07
194/286 (67.8)
140/237 (59.1)
13/17 (76.5)
98/123 (79.7)
266/363 (73.3)
160/220 (72.7)
98/142 (69.0)
47/83 (56.6)
243/468 (51.9)
185/406 (45.6)
a
!.001
!.001
!.001
.2
.06
.05
.3
.9
.4
.9
.6
.6
253/510 (49.6)
123/259 (47.5)
.4
235/367 (64.0)
53/90 (58.9)
.7
485/681 (71.2)
145/197 (73.6)
52/70 (74.3)
.09
396/800 (49.5)
26/67 (38.8)
180/283 (63.6)
110/175 (62.9)
431/601 (71.7)
124/168 (73.8)
.09
86/197 (43.7)
189/369 (51.2)
304/479 (63.5)
23/37 (62.2)
378/515 (73.4)
183/260 (70.4)
.006
232/446 (52.0)
95/214 (44.4)
24/72 (33.3)
61/106 (57.6)
140/204 (68.6)
628/870 (72.2)
47/71 (66.2)
!.001
48/131 (36.6)
58/109 (53.2)
77/145 (53.1)
151/258 (58.5)
50/113 (44.3)
35/82 (42.7)
8/35 (22.9)
185/279 (66.3)
76/132 (57.6)
22/39 (56.4)
141/204 (69.1)
288/378 (76.0)
.04
7/16 (43.8)
60/112 (53.6)
169/335 (50.5)
102/207 (49.3)
65/124 (52.4)
25/80 (31.3)
31/77 (40.3)
47/65 (72.3)
56/82 (68.3)
112/157 (72.3)
45/73 (61.6)
32/51 (62.8)
10/19 (52.6)
392/513 (76.4)
142/215 (66.1)
42/76 (55.3)
a
.002
6/9 (66.7)
46/59 (78.0)
127/201 (63.2)
92/133 (69.2)
43/75 (57.3)
20/46 (43.5)
70/131 (53.4)
89/111 (80.2)
119/152 (78.3)
209/263 (79.5)
84/114 (73.7)
57/86 (66.3)
16/39 (41.0)
.5
294/598 (49.2)
76/165 (46.1)
.9
247/384 (64.3)
67/108 (62.0)
20/31 (64.5)
.9
.6
291/609 (47.8)
102/196 (52.0)
35/69 (50.7)
.2
313/494 (63.4)
13/18 (72.2)
6/6 (100)
P
428/874 (49.0)
.04
.001a
641/888 (72.2)
26/36 (72.2)
13/19 (68.4)
P
.8
403/820 (49.2)
16/32 (50.0)
7/17 (41.2)
Isolates with restriction-fragment–length polymorphism patterns with !5 bands were excluded.
P value for trend.
main road was built in 1980. The 1029 patients had 406 RFLPdefined strains, giving a “diversity” of 39% (406/1029). Diversity in other long-term studies can be calculated similarly, as,
for example, 49% in Cape Town [11] and ∼70% in long-term
population-based studies in the West [8, 16, 20].
The effect of time period was explored using different time
windows. The proportion clustered when time windows were
484 • JID 2005:192 (1 August) • Glynn et al.
used was higher than the overall n ⫺ 1 clustering proportion
(59%), because the overall figure includes truncated time windows in the earlier years. This suggests that the proportion of
tuberculosis due to recent transmission is 165% (defining “recent” as within 5 years and using the 5-year time window).
When time windows were used, there was no evidence that the
proportion clustered changed during the period of this study.
Table 2.
Multivariate analysis of risk factors for clustering.
Age ⭓45 years
Age !45 years
OR (95% CI)
Group
Sex
Female
Male
HIV-infection status
Negative
Positive
Unknown
Area of residence
South
Central rural
Periurban
Urban
North
Far north
Outside district
Lived outside district during past 5 years
No
Yes, in Malawi
Yes, outside Malawi
Unknown
OR (95% CI)
a
No./total (%)
Unadjusted
Adjusted
No./total (%)
Unadjusted
Adjusteda
316/412 (76.7)
221/311 (71.1)
Ref.
0.75 (0.53–1.0)
Ref.
0.72 (0.50–1.0)
70/93 (75.3)
75/132 (56.8)
Ref.
0.43 (0.24–0.77)
Ref.
0.31 (0.15–0.62)
106/138 (76.8)
238/317 (75.1)
193/268 (72.0)
Ref.
0.91 (0.57–1.5)
0.78 (0.48–1.3)
Ref.
0.79 (0.48–1.3)
0.78 (0.45–1.3)
35/66 (53.0)
50/61 (82.0)
60/98 (61.2)
Ref.
4.0 (1.8–9.1)
1.4 (0.74 -2.6)
Ref.
5.1 (2.1–12.6)
2.3 (1.0–5.0)
49/98 (50.0)
69/84 (82.1)
94/116 (81.0)
171/211 (81.0)
71/89 (79.8)
42/61 (68.9)
12/27 (44.4)
0.23 (0.14–0.40)
1.1 (0.56–2.1)
1.0 (0.56–1.8)
Ref.
0.92 (0.50–1.7)
0.52 (0.27–0.98)
0.19 (0.08–0.43)
0.24 (0.14–0.41)
1.1 (0.54–2.1)
1.0 (0.56–1.8)
Ref.
0.85 (0.45–1.6)
0.48 (0.25–0.93)
0.30 (0.12–0.75)
21/33 (63.6)
20/27 (74.1)
25/36 (69.4)
38/52 (73.1)
13/25 (52.0)
15/25 (60.0)
4/12 (33.3)
0.64 (0.25–1.6)
1.1 (0.37–3.0)
0.84 (0.33–2.1)
Ref.
0.40 (0.15–1.1)
0.55 (0.20–1.5)
0.18 (0.05–0.71)
0.59 (0.21–1.6)
1.1 (0.34–3.4)
0.72 (0.25–2.0)
Ref.
0.38 (0.13–1.1)
0.76 (0.24–2.4)
0.12 (0.02–0.68)
304/377 (80.6)
116/180 (64.4)
33/56 (58.9)
84/110 (76.4)
Ref.
0.44 (0.29–0.65)
0.34 (0.19–0.62)
0.78 (0.47–1.3)
Ref.
0.51 (0.33–0.78)
0.46 (0.23–0.92)
0.92 (0.53–1.6)
88/136 (64.7)
26/35 (74.3)
9/20 (45.0)
22/34 (64.7)
Ref.
1.6 (0.68–3.6)
0.45 (0.17–1.2)
1.0 (0.46–2.2)
Ref.
1.6 (0.60–4.3)
0.55 (0.14–2.1)
0.44 (0.17–1.2)
NOTE. CI, confidence interval; OR, odds ratio; Ref., reference category. Isolates with restriction-fragment–length polymorphism patterns with !5 bands were excluded. Results show proportion
clustered (total clustering) and ORs for clustering.
a
Adjusted for other factors in the table and for year.
The way clustering increases over time reflects the incubation
period of tuberculosis, the rate of change of the RFLP pattern,
and population movement. The half-life for changes in RFLP
patterns has been estimated to be 2–3.2 years or longer [21–23]
and may be faster for transmission between patients than within
patients [14]. Modeling suggests that the time taken to reach a
plateau in clustering increases only slightly with increases in the
half-life of the RFLP pattern between 2 and 10 years [24]. Interestingly, the patterns of change in clustering over time seen
in Karonga were similar to those seen in populations with lower
tuberculosis incidences and lower overall clustering. Thus, clustering increased over time to reach a plateau at ∼3–4 years, as
in the Netherlands [8], and 72% of the clustering was found
within 1 year, as in San Francisco [5]. The consistency in time
taken to reach the plateau in different settings suggests that the
rate of change in clustering over time reflects the incubation
period of tuberculosis and the rate of change of the RFLP pattern
rather than local transmission patterns.
It was hoped that using retrospective clustering with limited
time periods or excluding smaller clusters would give clearer
associations between risk factors and clustering. The results
were similar in all analyses. The proportion clustered decreased
slightly with age. This is expected, since it reflects an increasing
proportion of reactivation disease with age and has been found
in other studies [8, 9]. However, the trend was seen only in
patients who were HIV negative. Similarly, an association between HIV-infection status and clustering was only found in
older adults, in whom HIV positivity was associated with a 5fold increased risk of clustering. HIV-infection status was not
known for all patients, but this is unlikely to have influenced
the association between HIV-infection status and clustering.
No association of clustering with HIV-infection status was found
in South Africa, in a general population or in the gold mines
[17, 25]. Where associations between clustering and HIV-infection status have been found, nosocomial transmission may
have been an important factor [1]. In Karonga, there was no
evidence that the HIV-related clustering was due to an outbreak:
the 50 HIV-positive older adults with clustered strains were in
35 different clusters.
Whether HIV infection is likely to increase clustering depends on its relative ability to increase the incidence of tuberculous disease after past or recent infection, on any influence
of HIV infection on risk of M. tuberculosis infection, and on
any difference in infectiousness between HIV-infected and -uninfected patients with tuberculosis. The finding of an association between HIV-infection status and clustering may suggest
that HIV infection has a greater effect on reinfection than on
reactivation disease. The absence of this association in patients
!45 years of age may be explained by the very high proportion
of disease attributable to recent transmission in the HIV-negative patients in the younger age group.
486 • JID 2005:192 (1 August) • Glynn et al.
We also found a strong association between clustering and
sex in older adults, with women being much more likely than
men to have clustered strains. This pattern is not usually found,
and some studies have found higher clustering in men [8, 9,
16]. The pattern is likely to depend on the local epidemiological
aspects of tuberculosis. We have previously shown in this population that a higher proportion of tuberculosis in women than
in men is attributable to transmission from a known contact,
so higher clustering might be expected [26].
The present study is, to our knowledge, the largest population-based molecular epidemiological study of tuberculosis
yet reported from a high-incidence setting and the first large
study in an area with a high prevalence of HIV infection. We
have shown that most of the tuberculosis in all age groups is
attributable to recent transmission and that HIV infection appears to increase the risk of tuberculosis after recent infection
more than that associated with reactivation of past infection,
at least in older adults.
Acknowledgments
We thank the Government of the Republic of Malawi for their interest
in and support of the project and the National Health Sciences Research
Committee of Malawi for permission to publish the article. We thank Emilia
Vynnycky for helpful comments on an earlier draft.
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