Limits...
Tuberculosis Epidemiology at the Country Scale: Self-Limiting Process and the HIV Effects.

Krsulovic FA, Lima M - PLoS ONE (2016)

Bottom Line: We found that overall the TB+HIV logistic model was more parsimonious than TB model alone, principally in the African region.Our results showed that HIV affected principally TB carrying capacity, as expected by the known HIV effects on TB natural-history.Based on our results, we suggest that the endogenous view should be considered as a plausible hypothesis to model and explain TB dynamics and that future World Health Organization reports could include the endogenous/exogenous framework as a supplement to help to decipher the main drivers of TB dynamics and other diseases.

View Article: PubMed Central - PubMed

Affiliation: Pontificia Universidad Católica de Chile, Santiago, Chile.

ABSTRACT

Background: The global spread of the human immunodeficiency virus (HIV) is the main hypothesis behind tuberculosis (TB) positive trends in the last decades, according to modeling studies and World Health Organization Reports (WHO). On one hand, TB (WHO) reports do not explicitly consider a modeling approach, but cover country and global TB trends. On the other hand, modeling studies usually do not cover the scale of WHO reports, because of the amount of parameters estimated to describe TB natural history. Here we combined these two principal sources of TB studies covering TB High Burden Countries (HBCs) dynamics. Our main goals were: (i) to detect the endogenous component of TB dynamics since 1974 for TB HBCs; and (ii) to explore the HIV exogenous effects on TB models`parameters.

Methods and findings: We explored the relationship between the TB per capita population rate of change (RI) and the infectious class size following an endogenous/exogenous framework. RI can be affected by intra-population processes (i.e. competition, predation) and exogenous variables like HIV. We found that TB dynamics had always a strong endogenous component, represented by a negative correlation between TB population size and RI, which was captured by the discrete logistic model. Moreover, we explored the HIV exogenous effects on TB models`parameters. We found that overall the TB+HIV logistic model was more parsimonious than TB model alone, principally in the African region. Our results showed that HIV affected principally TB carrying capacity, as expected by the known HIV effects on TB natural-history. We also tested if DOTS (Directly Observed Treatment Short-Course Strategy), poverty levels and BCG (Bacillus Calmette-Guérin) coverage explained the models´ residuals variances, but they did not.

Conclusions: Since 1974, TB dynamics were categorized in distinct chronological domains, with different dynamics but nearly the same underlying mechanism: a negative relationship between RI and infected class size (i.e. self-limiting). In the last decades, not only HIV spread represented a new TB chronological domain, but it also has been pushing TB carrying capacity (K) to higher levels. TB has a complex natural-history and imposes real challenges to model its dynamics. Yet, we were able to explore and reveal the main drivers of TB dynamics for HBCs since 1974, through a simple approach. Based on our results, we suggest that the endogenous view should be considered as a plausible hypothesis to model and explain TB dynamics and that future World Health Organization reports could include the endogenous/exogenous framework as a supplement to help to decipher the main drivers of TB dynamics and other diseases.

No MeSH data available.


Related in: MedlinePlus

RI-functions for each country and TB periods of growth for South Africa, Kenya, Mozambique, UR Tanzania, Zimbabwe, Brazil, Bangladesh, Cambodia and China.The symbols refer to the chronological RI periods: -○- the first, -Δ- the second, -+- the third and -●- the fourth. Only significant fits for the discrete models are shown with regression lines. RI negative trends for South Africa and Mozambique over the last years were excluded from RI-functions and analyses. The first period of TB growth for Tanzania was excluded to properly show the trends of acceleration and decline in RI. In Brazil, there is a clear cloud of data around zero, suggesting an underlying diminishing returns process between RI and TB cases.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4836699&req=5

pone.0153710.g002: RI-functions for each country and TB periods of growth for South Africa, Kenya, Mozambique, UR Tanzania, Zimbabwe, Brazil, Bangladesh, Cambodia and China.The symbols refer to the chronological RI periods: -○- the first, -Δ- the second, -+- the third and -●- the fourth. Only significant fits for the discrete models are shown with regression lines. RI negative trends for South Africa and Mozambique over the last years were excluded from RI-functions and analyses. The first period of TB growth for Tanzania was excluded to properly show the trends of acceleration and decline in RI. In Brazil, there is a clear cloud of data around zero, suggesting an underlying diminishing returns process between RI and TB cases.

Mentions: Model fits revealed that TB dynamics was always dominated by a first order negative correlation between RI and population size, which was captured by the discrete intra-specific competition model (Figs 1 and 2, S1 and S2 Figs, Table 1, S1 Table).


Tuberculosis Epidemiology at the Country Scale: Self-Limiting Process and the HIV Effects.

Krsulovic FA, Lima M - PLoS ONE (2016)

RI-functions for each country and TB periods of growth for South Africa, Kenya, Mozambique, UR Tanzania, Zimbabwe, Brazil, Bangladesh, Cambodia and China.The symbols refer to the chronological RI periods: -○- the first, -Δ- the second, -+- the third and -●- the fourth. Only significant fits for the discrete models are shown with regression lines. RI negative trends for South Africa and Mozambique over the last years were excluded from RI-functions and analyses. The first period of TB growth for Tanzania was excluded to properly show the trends of acceleration and decline in RI. In Brazil, there is a clear cloud of data around zero, suggesting an underlying diminishing returns process between RI and TB cases.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4836699&req=5

pone.0153710.g002: RI-functions for each country and TB periods of growth for South Africa, Kenya, Mozambique, UR Tanzania, Zimbabwe, Brazil, Bangladesh, Cambodia and China.The symbols refer to the chronological RI periods: -○- the first, -Δ- the second, -+- the third and -●- the fourth. Only significant fits for the discrete models are shown with regression lines. RI negative trends for South Africa and Mozambique over the last years were excluded from RI-functions and analyses. The first period of TB growth for Tanzania was excluded to properly show the trends of acceleration and decline in RI. In Brazil, there is a clear cloud of data around zero, suggesting an underlying diminishing returns process between RI and TB cases.
Mentions: Model fits revealed that TB dynamics was always dominated by a first order negative correlation between RI and population size, which was captured by the discrete intra-specific competition model (Figs 1 and 2, S1 and S2 Figs, Table 1, S1 Table).

Bottom Line: We found that overall the TB+HIV logistic model was more parsimonious than TB model alone, principally in the African region.Our results showed that HIV affected principally TB carrying capacity, as expected by the known HIV effects on TB natural-history.Based on our results, we suggest that the endogenous view should be considered as a plausible hypothesis to model and explain TB dynamics and that future World Health Organization reports could include the endogenous/exogenous framework as a supplement to help to decipher the main drivers of TB dynamics and other diseases.

View Article: PubMed Central - PubMed

Affiliation: Pontificia Universidad Católica de Chile, Santiago, Chile.

ABSTRACT

Background: The global spread of the human immunodeficiency virus (HIV) is the main hypothesis behind tuberculosis (TB) positive trends in the last decades, according to modeling studies and World Health Organization Reports (WHO). On one hand, TB (WHO) reports do not explicitly consider a modeling approach, but cover country and global TB trends. On the other hand, modeling studies usually do not cover the scale of WHO reports, because of the amount of parameters estimated to describe TB natural history. Here we combined these two principal sources of TB studies covering TB High Burden Countries (HBCs) dynamics. Our main goals were: (i) to detect the endogenous component of TB dynamics since 1974 for TB HBCs; and (ii) to explore the HIV exogenous effects on TB models`parameters.

Methods and findings: We explored the relationship between the TB per capita population rate of change (RI) and the infectious class size following an endogenous/exogenous framework. RI can be affected by intra-population processes (i.e. competition, predation) and exogenous variables like HIV. We found that TB dynamics had always a strong endogenous component, represented by a negative correlation between TB population size and RI, which was captured by the discrete logistic model. Moreover, we explored the HIV exogenous effects on TB models`parameters. We found that overall the TB+HIV logistic model was more parsimonious than TB model alone, principally in the African region. Our results showed that HIV affected principally TB carrying capacity, as expected by the known HIV effects on TB natural-history. We also tested if DOTS (Directly Observed Treatment Short-Course Strategy), poverty levels and BCG (Bacillus Calmette-Guérin) coverage explained the models´ residuals variances, but they did not.

Conclusions: Since 1974, TB dynamics were categorized in distinct chronological domains, with different dynamics but nearly the same underlying mechanism: a negative relationship between RI and infected class size (i.e. self-limiting). In the last decades, not only HIV spread represented a new TB chronological domain, but it also has been pushing TB carrying capacity (K) to higher levels. TB has a complex natural-history and imposes real challenges to model its dynamics. Yet, we were able to explore and reveal the main drivers of TB dynamics for HBCs since 1974, through a simple approach. Based on our results, we suggest that the endogenous view should be considered as a plausible hypothesis to model and explain TB dynamics and that future World Health Organization reports could include the endogenous/exogenous framework as a supplement to help to decipher the main drivers of TB dynamics and other diseases.

No MeSH data available.


Related in: MedlinePlus