29
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Modelling the Impact of Artemisinin Combination Therapy and Long-Acting Treatments on Malaria Transmission Intensity

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Artemisinin derivatives used in recently introduced combination therapies (ACTs) for Plasmodium falciparum malaria significantly lower patient infectiousness and have the potential to reduce population-level transmission of the parasite. With the increased interest in malaria elimination, understanding the impact on transmission of ACT and other antimalarial drugs with different pharmacodynamics becomes a key issue. This study estimates the reduction in transmission that may be achieved by introducing different types of treatment for symptomatic P. falciparum malaria in endemic areas.

          Methods and Findings

          We developed a mathematical model to predict the potential impact on transmission outcomes of introducing ACT as first-line treatment for uncomplicated malaria in six areas of varying transmission intensity in Tanzania. We also estimated the impact that could be achieved by antimalarials with different efficacy, prophylactic time, and gametocytocidal effects. Rates of treatment, asymptomatic infection, and symptomatic infection in the six study areas were estimated using the model together with data from a cross-sectional survey of 5,667 individuals conducted prior to policy change from sulfadoxine-pyrimethamine to ACT. The effects of ACT and other drug types on gametocytaemia and infectiousness to mosquitoes were independently estimated from clinical trial data. Predicted percentage reductions in prevalence of infection and incidence of clinical episodes achieved by ACT were highest in the areas with low initial transmission. A 53% reduction in prevalence of infection was seen if 100% of current treatment was switched to ACT in the area where baseline slide-prevalence of parasitaemia was lowest (3.7%), compared to an 11% reduction in the highest-transmission setting (baseline slide prevalence = 57.1%). Estimated percentage reductions in incidence of clinical episodes were similar. The absolute size of the public health impact, however, was greater in the highest-transmission area, with 54 clinical episodes per 100 persons per year averted compared to five per 100 persons per year in the lowest-transmission area. High coverage was important. Reducing presumptive treatment through improved diagnosis substantially reduced the number of treatment courses required per clinical episode averted in the lower-transmission settings although there was some loss of overall impact on transmission. An efficacious antimalarial regimen with no specific gametocytocidal properties but a long prophylactic time was estimated to be more effective at reducing transmission than a short-acting ACT in the highest-transmission setting.

          Conclusions

          Our results suggest that ACTs have the potential for transmission reductions approaching those achieved by insecticide-treated nets in lower-transmission settings. ACT partner drugs and nonartemisinin regimens with longer prophylactic times could result in a larger impact in higher-transmission settings, although their long term benefit must be evaluated in relation to the risk of development of parasite resistance.

          Abstract

          Lucy Okell and colleagues predict the impact on transmission outcomes of ACT as first-line treatment for uncomplicated malaria in six areas of varying transmission intensity in Tanzania.

          Editors' Summary

          Background.

          Plasmodium falciparum, a mosquito-borne parasite that causes malaria, kills nearly one million people every year. When an infected mosquito bites a person, it injects a life stage of the parasite called sporozoites, which invade human liver cells where they initially develop. The liver cells then release merozoites (another life stage of the parasite). These invade red blood cells where they multiply before bursting out and infecting more red blood cells, which can cause fever and damage vital organs. Some merozoites develop into gametocytes, which infect mosquitos when they take a blood meal. In the mosquito, the gametocytes give rise to sporozoites, thus completing the parasite's life cycle. Because malaria parasites are now resistant to many antimalarial drugs, the preferred first-line treatment for P. falciparum malaria in most countries is artemisinin combination therapy (ACT). Artemisinin derivatives are fast-acting antimalarial agents that, unlike previous first-line treatments, reduce the number of gametocytes in patients' blood, making them less infectious to mosquitos, and therefore have more potential to reduce malaria transmission. These compounds are used in combination with another antimalarial drug to reduce the chances of P. falciparum becoming resistant to either drug.

          Why Was This Study Done?

          Because malaria poses such a large global public-health burden, there is considerable national and international interest in eliminating it or at least minimizing its transmission. Malaria control agencies need to know how to choose between available types of ACT as well as other antimalarials so as to not only cure malaria illness but also prevent transmission as much as possible. The financial resources available to control malaria are limited, so for planning integrated transmission reduction programs it is important for policy makers to know what contribution their treatment policy could make in addition to other control strategies (for example, the provision of insecticide-treated bed nets to reduce mosquito bites) to reducing transmission. Furthermore, in areas with high levels of malaria, it is uncertain to what extent treatment can reduce transmission since many infected people are immune and do not suffer symptoms or seek health care, but continue to transmit to others. In this study, the researchers develop a mathematical model to predict the impact on malaria transmission of the introduction of ACT and alternative first-line treatments for malaria in six regions of Tanzania with different levels of malaria transmission.

          What Did the Researchers Do and Find?

          The researchers developed a “deterministic compartmental” model of malaria transmission in human and mosquito populations and included numerous variables likely to affect malaria transmission (variables were based on data collected in Tanzania just before the introduction of ACT). They then used the model to estimate the impact on malaria transmission of introducing ACT or other antimalarial drugs with different properties. The model predicted that the percentage reduction in the prevalence of infection (the fraction of the population with malaria) and the incidence of infection (the number of new cases in the population per year) associated with a 100% switch to ACT would be greater in areas with low initial transmission rates than in areas with high transmission rates. For example, in the area with the lowest initial transmission rates, the model predicted that the prevalence of infection would drop by 53%, but in the area with the highest initial transmission rate, the drop would be only 11%. However, because more people get malaria in high-transmission areas, the total number of malaria illness episodes prevented would be ten times higher in the area with highest transmission than in the area with lowest transmission. The model also predicted that, in areas with high transmission, long-acting treatments which protect patients from reinfection would reduce transmission more effectively than some common currently used ACT regimens which are gametocyte-killing but short-acting. Treatments which were both long-acting and gametocyte-killing were predicted to have the biggest impact across all settings.

          What Do These Findings Mean?

          As with all mathematical models, the accuracy of the predictions made by this model depend on the many assumptions incorporated into the model. In addition, because data from Tanzania were fed into the model, its predictions are to some extent specific to the area. Nevertheless the Tanzanian setting is typical of sub-Saharan malaria-affected areas, and the authors show that varying their assumptions and the data fed into the model within realistic ranges in most cases does not substantially change their overall conclusions. The findings in this study suggest that in low-transmission areas, provided ACT is widely used, ACT may reduce malaria transmission as effectively as the widespread use of insecticide-treated bed nets. The findings also suggest that the use of longer-acting regimens with or without artemisinin components might be a good way to reduce transmission in high-transmission areas, provided the development of parasite resistance can be avoided. More generally, these findings suggest that public-health officials need to take the properties of antimalarial drugs into account together with the levels of transmission in the area when designing policies in order to achieve the highest impact on malaria transmission.

          Additional Information.

          Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0050226.

          Related collections

          Most cited references60

          • Record: found
          • Abstract: found
          • Article: not found

          Heterogeneities in the transmission of infectious agents: implications for the design of control programs.

          From an analysis of the distributions of measures of transmission rates among hosts, we identify an empirical relationship suggesting that, typically, 20% of the host population contributes at least 80% of the net transmission potential, as measured by the basic reproduction number, R0. This is an example of a statistical pattern known as the 20/80 rule. The rule applies to a variety of disease systems, including vector-borne parasites and sexually transmitted pathogens. The rule implies that control programs targeted at the "core" 20% group are potentially highly effective and, conversely, that programs that fail to reach all of this group will be much less effective than expected in reducing levels of infection in the population as a whole.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            The entomological inoculation rate and Plasmodium falciparum infection in African children.

            Malaria is an important cause of global morbidity and mortality. The fact that some people are bitten more often than others has a large effect on the relationship between risk factors and prevalence of vector-borne diseases. Here we develop a mathematical framework that allows us to estimate the heterogeneity of infection rates from the relationship between rates of infectious bites and community prevalence. We apply this framework to a large, published data set that combines malaria measurements from more than 90 communities. We find strong evidence that heterogeneous biting or heterogeneous susceptibility to infection are important and pervasive factors determining the prevalence of infection: 20% of people receive 80% of all infections. We also find that individual infections last about six months on average, per infectious bite, and children who clear infections are not immune to new infections. The results have important implications for public health interventions: the success of malaria control will depend heavily on whether efforts are targeted at those who are most at risk of infection.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              The decline in paediatric malaria admissions on the coast of Kenya

              Background There is only limited information on the health impact of expanded coverage of malaria control and preventative strategies in Africa. Methods Paediatric admission data were assembled over 8.25 years from three District Hospitals; Kilifi, Msambweni and Malindi, situated along the Kenyan Coast. Trends in monthly malaria admissions between January 1999 and March 2007 were analysed using several time-series models that adjusted for monthly non-malaria admission rates and the seasonality and trends in rainfall. Results Since January 1999 paediatric malaria admissions have significantly declined at all hospitals. This trend was observed against a background of rising or constant non-malaria admissions and unaffected by long-term rainfall throughout the surveillance period. By March 2007 the estimated proportional decline in malaria cases was 63% in Kilifi, 53% in Kwale and 28% in Malindi. Time-series models strongly suggest that the observed decline in malaria admissions was a result of malaria-specific control efforts in the hospital catchment areas. Conclusion This study provides evidence of a changing disease burden on the Kenyan coast and that the most parsimonious explanation is an expansion in the coverage of interventions such as the use of insecticide-treated nets and the availability of anti-malarial medicines. While specific attribution to intervention coverage cannot be computed what is clear is that this area of Kenya is experiencing a malaria epidemiological transition.
                Bookmark

                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS Med
                pmed
                plme
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, USA )
                1549-1277
                1549-1676
                November 2008
                25 November 2008
                : 5
                : 11
                : e226
                Affiliations
                [1 ] Department of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
                [2 ] Department of Medical Microbiology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
                [3 ] MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
                Hong Kong University, Hong Kong
                Author notes
                * To whom correspondence should be addressed. E-mail: Lucy.Okell@ 123456lshtm.ac.uk
                Article
                08-PLME-RA-1732R2 plme-05-11-15
                10.1371/journal.pmed.0050226
                2586356
                19067479
                b8759752-865d-4b95-b4b1-77f64219d5ee
                Copyright: © 2008 Okell et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 20 June 2008
                : 2 October 2008
                Page count
                Pages: 12
                Categories
                Research Article
                Computational Biology
                Mathematics
                Public Health and Epidemiology
                Malaria
                Global Health
                Statistics
                Health Policy
                Medicine in Developing Countries
                Custom metadata
                Okell LC, Drakeley CJ, Bousema T, Whitty CJM, Ghani AC (2008) Modelling the impact of artemisinin combination therapy and long-acting treatments on malaria transmission intensity. PLoS Med 5(11): e226. doi: 10.1371/journal.pmed.0050226

                Medicine
                Medicine

                Comments

                Comment on this article