Limits...
The dynamics, causes and possible prevention of Hepatitis E outbreaks.

Nannyonga B, Sumpter DJ, Mugisha JY, Luboobi LS - PLoS ONE (2012)

Bottom Line: The dynamics and the factors causing outbreaks of these diseases can be better understood using mathematical models, which are fit to data.First, we use the data to determine that R0 is approximately 2.25 for the outbreak.Secondly, we use a model to estimate that the critical level of latrine and bore hole coverages needed to eradicate the epidemic is at least 16% and 17% respectively.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematics, Makerere University, Kampala, Uganda. bnk@math.mak.ac.ug

ABSTRACT
Rapidly spreading infectious diseases are a serious risk to public health. The dynamics and the factors causing outbreaks of these diseases can be better understood using mathematical models, which are fit to data. Here we investigate the dynamics of a Hepatitis E outbreak in the Kitgum region of northern Uganda during 2007 to 2009. First, we use the data to determine that R0 is approximately 2.25 for the outbreak. Secondly, we use a model to estimate that the critical level of latrine and bore hole coverages needed to eradicate the epidemic is at least 16% and 17% respectively. Lastly, we further investigate the relationship between the co-infection factor for malaria and Hepatitis E on the value of R0 for Hepatitis E. Taken together, these results provide us with a better understanding of the dynamics and possible causes of Hepatitis E outbreaks.

Show MeSH

Related in: MedlinePlus

Evolutin of infection with time: Malaria infected, M, are represented by the magenta line, the Exposed, E, by blue, and the Infected, I by the red line.Figure (b) shows the phase space portrait in the S-I plane.  is 2, , and . Other parameter values are given in Table 2.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC3404073&req=5

pone-0041135-g002: Evolutin of infection with time: Malaria infected, M, are represented by the magenta line, the Exposed, E, by blue, and the Infected, I by the red line.Figure (b) shows the phase space portrait in the S-I plane. is 2, , and . Other parameter values are given in Table 2.

Mentions: Under the above assumption, equations (7) are rewritten to incorporate the malaria dynamics in equation (11) as follows:(13)where is a parameter that models change the increase (or decrease) in susceptibility to Hepatitis E of malaria infected individuals [12]. The other parameters are as defined in equations (7) and remain as defined there. We assume here that after exposure to HEV, both the susceptible and malaria infected groups join the exposed, E and subsequently the I group. In other words, individuals that harbor both infections are assumed to develop HEV symptoms at the same speed as those with only HEV. The dynamics of this model for standard parameter values are shown in Figure 2.


The dynamics, causes and possible prevention of Hepatitis E outbreaks.

Nannyonga B, Sumpter DJ, Mugisha JY, Luboobi LS - PLoS ONE (2012)

Evolutin of infection with time: Malaria infected, M, are represented by the magenta line, the Exposed, E, by blue, and the Infected, I by the red line.Figure (b) shows the phase space portrait in the S-I plane.  is 2, , and . Other parameter values are given in Table 2.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3404073&req=5

pone-0041135-g002: Evolutin of infection with time: Malaria infected, M, are represented by the magenta line, the Exposed, E, by blue, and the Infected, I by the red line.Figure (b) shows the phase space portrait in the S-I plane. is 2, , and . Other parameter values are given in Table 2.
Mentions: Under the above assumption, equations (7) are rewritten to incorporate the malaria dynamics in equation (11) as follows:(13)where is a parameter that models change the increase (or decrease) in susceptibility to Hepatitis E of malaria infected individuals [12]. The other parameters are as defined in equations (7) and remain as defined there. We assume here that after exposure to HEV, both the susceptible and malaria infected groups join the exposed, E and subsequently the I group. In other words, individuals that harbor both infections are assumed to develop HEV symptoms at the same speed as those with only HEV. The dynamics of this model for standard parameter values are shown in Figure 2.

Bottom Line: The dynamics and the factors causing outbreaks of these diseases can be better understood using mathematical models, which are fit to data.First, we use the data to determine that R0 is approximately 2.25 for the outbreak.Secondly, we use a model to estimate that the critical level of latrine and bore hole coverages needed to eradicate the epidemic is at least 16% and 17% respectively.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematics, Makerere University, Kampala, Uganda. bnk@math.mak.ac.ug

ABSTRACT
Rapidly spreading infectious diseases are a serious risk to public health. The dynamics and the factors causing outbreaks of these diseases can be better understood using mathematical models, which are fit to data. Here we investigate the dynamics of a Hepatitis E outbreak in the Kitgum region of northern Uganda during 2007 to 2009. First, we use the data to determine that R0 is approximately 2.25 for the outbreak. Secondly, we use a model to estimate that the critical level of latrine and bore hole coverages needed to eradicate the epidemic is at least 16% and 17% respectively. Lastly, we further investigate the relationship between the co-infection factor for malaria and Hepatitis E on the value of R0 for Hepatitis E. Taken together, these results provide us with a better understanding of the dynamics and possible causes of Hepatitis E outbreaks.

Show MeSH
Related in: MedlinePlus