Lagged effects of rainfall on malaria: a case study of Meghalaya

Background: Meghalaya contributes about twenty per cent of India's total malaria death and is one of the high malaria endemic states in India, very susceptible to malaria transmission mainly due to favorable climatic conditions that mostly facilitate the transmission. In the relationship between malaria and meteorological factors, existing studies mainly focus on the interaction between different climatic factors, while interaction within one specific climatic predictor at different ag times has been largely neglected. This paper aims to explore the interaction of lagged rainfalls and their impact on malaria incidence. Methods: The district monthly malaria records from Jan 2005 to December 2017 was collected from the Department of Health Services (Malaria), Government of Meghalaya. The district monthly meteorological records from Jan 2005 to December 2017 was collected from the Directorate of Agriculture, Government of Meghalaya, in which average temperature (℃), humidity (%) and rainfall (mm) had been recorded. Monthly malaria cases and three climatic variables of 4 districts in Meghalaya from 2015 to 2017 were analysed with the varying coefficient-distributed lag non-linear model. The missing climatic values were imputed using Kalman Smoothing on structural time series using the package imputeTS in R. Results: During the period 2005-2017, a total of 309133 malaria cases were reported in all the districts under study. The monthly average rainfall ranges from a minimum of 181.79 mm in South Garo to a maximum of 367.87 in Jaintia. Also, South Garo and East Khasi are the hottest and the coolest place understudy with 26.96 and 16.86 degrees Celsius respectively. Rainfall levels in the first-month lag affect the non-linear patterns between the incidence of malaria and rainfall at each lag time. The low rainfall level at the first-month lag may promote malaria incidence as rainfall increases. However, for the high rainfall level at the first-month lag, malaria incidence decreases as rainfall increases. Conclusion: The interaction effect between lagged rainfalls on malaria incidence was observed in this study, and highlights its importance for future studies to better understand and predict malaria transmission.

Classifying Features Persuading the Use of Long Lasting Insecticide Treated Nets (LLINs) and Its Implications in Exterminating the Incidence of Malaria-Death in Ghana

This is a cross-sectional quantitative study purported to identify features deemed to persuade the usage of LLINs in exterminating incidences of malaria-death in Ghana. The population consisted of mothers and caregivers of children under five in Asamankese a district in the Eastern region of Ghana. Questionnaires were developed based on the profile and the set of study objectives, it sought information on socio-economic variables, knowledge level on LLINs, and influence of climatic and environmental factors on LLINs usage. Data were coded and keyed into SPSS version 20. Frequencies, percentages, means, standard deviations, graphs and tables were used to explore the data. Chi-square test was used to do further investigation. It was revealed that LLINs usage was influenced by a group of features including: background characteristics of household; socio-economic variables, environmental variables and knowledge on importance of LLINs. There was an association between LLINs usage and monthly income of caregivers (p<0.05). Furthermore, there was a significant relationship (p<0.05) between environmental features and LLINs usage. There was a relationship (p<0.05) between one’s knowledge and use of LLINs. In addition, there was a relationship between usage and the number of times per month visits were made to the hospitals for health care. Environmental factors permitted the use of LLINs, Eighty-six (86%) of the respondents who used LLINs did use it because the weather aided them. It is recommended that behavior change education be intensified in the region so that more people can accept and adopt a lifestyle that will protect them from the deadly malaria diseases. Efforts must be made by the major players in the health sector to make the net readily available in the communities at low prices to enable the ordinary Ghanaian to purchase it.

Malaria Parasite Diagnosis Using Computational Techniques: A Comprehensive Review

Malaria is a very serious disease that caused by the transmitted of parasites through the bites of infected Anopheles mosquito. Malaria death cases can be reduced and prevented through early diagnosis and prompt treatment. A fast and easy-to-use method, with high performance is required to differentiate malaria from non-malarial fevers. Manual examination of blood smears is currently the gold standard, but it is time-consuming, labour-intensive, requires skilled microscopists and the sensitivity of the method depends heavily on the skills of the microscopist. Currently, microscopy-based diagnosis remains the most widely used approach for malaria diagnosis. The development of automated malaria detection techniques is still a field of interest. Automated detection is faster and high accuracy compared to the traditional technique using microscopy. This paper presents an exhaustive review of these studies and suggests a direction for future developments of the malaria detection techniques. This paper analysis of three popular computational approaches which is k-mean clustering, neural network, and morphological approach was presented. Based on overall performance, many research proposed based on the morphological approach in order to detect malaria.

Trends in Malaria Indicators After Scale-Up of Community-Based Malaria Management in Afghanistan

Objectives: The Community-Based Malaria Management (CBMM) strategy, introduced in 2013 and expanded to all health facilities and health posts in Afghanistan by 2016, aimed to deliver rapid diagnostic testing and more timely treatment to all communities nationwide. In this study, we compared the trends in several malaria outcome indicators before and after the expansion of the CBMM strategy.Study Design: Cross-sectional analysis of surveillance data Methods: Generalized estimating equation (GEE) models with a Poisson distribution were used to assess trends of three key outcomes before (2012-2015) and after (2016-2019) CBMM expansion. These outcomes were annual malaria incidence rate (both all and confirmed malaria incidence), malaria death rate, and malaria test positivity rate. Additional variables assessed included annual blood examination rates (ABER) and malaria confirmation rate.Results: Average malaria incidence rates decreased from 13.1 before CBMM expansion to 10.0 per 1000 persons per year after CBMM expansion (P<0.001). The time period after CBMM was expanded witnessed a 339% increase in confirmed malaria incidence as compared to the period before (IRR 3.39, 95% CI 2.18, 5.27; P<0.001). In the period since the expansion of CBMM (2016-2019), overall malaria incidence rate declined by 19% each year (IRR 0.81, 95% CI 0.71,0.92; P=0.001) and the malaria death rate declined by 85% each year (IRR 0.15, 95% CI 0.12, 0.20; P<0.001). In comparing the before period to the after period, the ABER increased from 2.3 to 3.5 per 100 person/year, the malaria test positivity rate increased from 12.2% to 20.5%, and the confirmation rate increased from 21% before to 71% after CBMM.Conclusions: Afghanistan’s CBMM expansion to introduce rapid diagnostic tests and provide more timely treatment for malaria through all levels of care temporally correlates with significant improvement in multiple indicators of malaria control.

Investigation of a child malaria death during COVID-19 pandemic in a hamlet of Angul district, Odisha (India)

Background: This study aimed to find out the cause of child death due to Plasmodium falciparum and associate co-morbidities in a hamlet of Garud village of central district of Odisha (India), Angul during the COVID-19 pandemic and to recommend necessary actions to prevent such unwanted death.Methods: A retrospective investigation was conducted bases on the death audit report of a female child belonging to Garud village of Angul district. Death was reported at the district headquarters hospital, Angul. Detailed history from the starting of first symptom till death with laboratory investigations were reviewed using the malaria death audit format of NVBDCP, Odisha. Along with in-depth interview with family members, mass screening using bivalent rapid test and slide test, treatment and malaria preventive measures were undertaken in the community.Results: During the COVID-19 pandemic, one child death was recorded due to falciparum malaria infection. Along with the child, all two family members were infected with falciparum. The family belongs to small hamlet with eight households and 39 population. All 39 populations were screened for malaria and out of these, 11 number people were found positive of falciparum.Conclusions: COVID-19 pandemic resulted the major societal disruption due to lockdown and shutdowns affecting routine health care which may be attributed to the death of a child even in a in a well-resource setting district of Odisha. In such pandemic situation much more attention need to be given on the traditional infectious diseases which may cause unnoticed death.

Analysis of Trend of Malaria Prevalence in the Ten Asian Countries from 2006 to 2011: A Longitudinal Study

Background. To control the malaria mortality, the global and national communities have worked together and produced impressive results in the world. Some of the Asian counties’ malaria mortality rate is more compared to countries with high health facilities around the world. This paper’s main aim is to describe trend of malaria cases and mortality in 10 Asian countries using the World Health Organization data. Methods. Malaria mortality data was collected systematically from WHO and UN database for the period 2006–2011. We estimated malaria mortality by age and countries. We also explored the dynamic relationships among malaria death rate, total populations, and geographical region using a map. During 2006–2011, the average malaria death per 10,000 population of all ages was 0.239 (95% CI 0.104 to 0.373), of children aged less than 5 year 1.143 (0.598 to 1.687), and of age greater than 5 years 0.089 (0.043 to 0.137) in Asian countries. Malaria prevalence per 10,000 populations steadily decreased from 486.7 in 2006 to 298.9 in 2011. Conclusion. The findings show that malaria mortality is higher for children aged less than 5 years compared with with adults selected in Asian countries except Sri Lanka.