26
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Malaria mortality characterization and the relationship between malaria mortality and climate in Chimoio, Mozambique

      research-article

      Read this article at

      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

          The United Nation’s sustainable development goal for 2030 is to eradicate the global malaria epidemic, primarily as the disease continues to be one of the major concerns for public health in sub-Saharan Africa. In 2015, the region accounted for 90% of malaria deaths. Mozambique recorded a malaria mortality rate of 42.75 (per 100,000). In Chimoio, Mozambique’s fifth largest city, malaria is the fourth leading cause of death (9.4%). Few data on malaria mortality exists in Mozambique, particularly in relation to Chimoio. The objective of this study was to characterize malaria mortality trends and its spatial distribution in Chimoio.

          Methods

          Malaria mortality data and climate data were extracted from the Chimoio Civil Registration records, and the Regional Weather station, from 2010 to 2014. The malaria crude mortality rate was calculated. ANOVA, Tukey’s, Chi square, and time series were carried out and an intervention analysis ARIMA model developed.

          Results

          A total of 944 malaria death cases were registered in Chimoio, 729 of these among Chimoio residents (77%). The average malaria mortality by gender was 44.9% for females and 55.1% for males. The age of death varied from 0 to 96 years, with an average age of 25.9 (SE = 0.79) years old. January presented the highest average of malaria deaths, and urban areas presented a lower crude malaria mortality rate. Rural neighbourhoods with good accessibility present the highest malaria crude mortality rate, over 85 per 100,000. Seasonal ARMA (2,0)(1,0) 12 fitted the data although it was not able to capture malaria mortality peaks occurring during malaria outbreaks. Intervention effect properly fit the mortality peaks and reduced ARMA’s root mean square error by almost 25%.

          Conclusion

          Malaria mortality is increasing in Chimoio; children between 1 and 4 years old represent 13% of Chimoio population, but account for 25% of malaria mortality. Malaria mortality shows seasonal and spatial characteristics. More studies should be carried out for malaria eradication in the municipality.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12936-017-1866-0) contains supplementary material, which is available to authorized users.

          Related collections

          Most cited references16

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

          Intervention Analysis with Applications to Economic and Environmental Problems

          G. BOX, G. Tiao (1975)
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Forecasting malaria incidence based on monthly case reports and environmental factors in Karuzi, Burundi, 1997–2003

            Background The objective of this work was to develop a model to predict malaria incidence in an area of unstable transmission by studying the association between environmental variables and disease dynamics. Methods The study was carried out in Karuzi, a province in the Burundi highlands, using time series of monthly notifications of malaria cases from local health facilities, data from rain and temperature records, and the normalized difference vegetation index (NDVI). Using autoregressive integrated moving average (ARIMA) methodology, a model showing the relation between monthly notifications of malaria cases and the environmental variables was developed. Results The best forecasting model (R2 adj = 82%, p < 0.0001 and 93% forecasting accuracy in the range ± 4 cases per 100 inhabitants) included the NDVI, mean maximum temperature, rainfall and number of malaria cases in the preceding month. Conclusion This model is a simple and useful tool for producing reasonably reliable forecasts of the malaria incidence rate in the study area.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Changes in malaria morbidity and mortality in Mpumalanga Province, South Africa (2001- 2009): a retrospective study

              Background Malaria remains a serious epidemic threat in Mpumalanga Province. In order to appropriately target interventions to achieve substantial reduction in the burden of malaria and ultimately eliminate the disease, there is a need to track progress of malaria control efforts by assessing the time trends and evaluating the impact of current control interventions. This study aimed to assess the changes in the burden of malaria in Mpumalanga Province during the past eight malaria seasons (2001/02 to 2008/09) and whether indoor residual spraying (IRS) and climate variability had an effect on these changes. Methods This is a descriptive retrospective study based on the analysis of secondary malaria surveillance data (cases and deaths) in Mpumalanga Province. Data were extracted from the Integrated Malaria Information System. Time series model (Autoregressive Integrated Moving Average) was used to assess the association between climate and malaria. Results Within the study period, a total of 35,191 cases and 164 deaths due to malaria were notified in Mpumalanga Province. There was a significant decrease in the incidence of malaria from 385 in 2001/02 to 50 cases per 100,000 population in 2008/09 (P 65 years, with the mean CFR of 2.1% as compared to the national target of 0.5%. A distinct seasonal transmission pattern was found to be significantly related to changes in rainfall patterns (P = 0.007). A notable decline in malaria case notification was observed following apparent scale-up of IRS coverage from 2006/07 to 2008/09 malaria seasons. Conclusions Mpumalanga Province has achieved the goal of reducing malaria morbidity and mortality by over 70%, partly as a result of scale-up of IRS intervention in combination with other control strategies. These results highlight the need to continue with IRS together with other control strategies until interruption in local malaria transmission is completely achieved. However, the goal to eliminate malaria as a public health problem requires efforts to be directed towards the control of imported malaria cases; development of strategies to interrupt local transmission; and maintaining high quality surveillance and reporting system.
                Bookmark

                Author and article information

                Contributors
                jferrao@ucm.ac.mz
                jmm@novaims.unl.pt
                painho@novaims.unl.pt
                707140268@ucm.ac.mz
                Journal
                Malar J
                Malar. J
                Malaria Journal
                BioMed Central (London )
                1475-2875
                22 May 2017
                22 May 2017
                2017
                : 16
                : 212
                Affiliations
                [1 ]ISNI 0000 0004 0397 1777, GRID grid.287982.e, Faculdade de Engenharia, , Universidade Católica de Moçambique, ; Chimoio, Mozambique
                [2 ]ISNI 0000000121511713, GRID grid.10772.33, NOVA Information Management School, , NOVA University of Lisbon, ; Lisbon, Portugal
                [3 ]Direccao Provincial de Saúde de Manica, Lisbon, Mozambique
                Article
                1866
                10.1186/s12936-017-1866-0
                5440990
                28532410
                1a7b12fe-3ecf-4a80-bb6f-8289a097d198
                © The Author(s) 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 23 October 2016
                : 15 May 2017
                Categories
                Research
                Custom metadata
                © The Author(s) 2017

                Infectious disease & Microbiology
                malaria mortality,seasonality,spatiality,chimoio,precision public health

                Comments

                Comment on this article