Climatic variables and malaria transmission dynamics in Jimma town, South West Ethiopia

Perceived causes and solutions for malaria prevalence among seasonal migrant workers in Northwest Ethiopia: a qualitative study

BACKGROUND

Seasonal migrant workers are at increased risk of malaria and can play a substantial role in transmitting the disease to receptive areas. Assessments conducted among these workers showed a high prevalence of malaria. This qualitative study aimed to explore the contributing factors and challenges to the high malaria prevalence among seasonal migrant workers in agricultural farm areas. The study also sought to identify potential solutions.

METHODS

A descriptive phenomenological approach was employed to investigate the perceived causes, challenges, and solutions related to malaria prevalence among seasonal migrant workers in the development corridors of southwest Ethiopia. This approach emphasizes describing experiences as they are, without researcher interpretation. Data were gathered from 24 individuals purposefully selected for their close involvement with seasonal migrant workers and their experience with malaria issues in agricultural farm areas. Open-ended questions were used, and interviews were conducted in safe, quiet settings. Data management was performed using Open Code software version 4.03, and thematic analysis was applied to the contents.

RESULTS

The study findings identified origin from highland areas, low health-seeking behaviour, working at night, and lack of use of long-lasting insecticidal nets (LLINs) as the perceived causes of high malaria prevalence among seasonal migrant workers by the study participants. Limited collaboration among stakeholders, a lack of migrant-friendly malaria prevention strategies, and inconsistent support for medical supplies were challenges highlighted by the key informants. Therefore, seasonal migrant workers were faced with high risk of malaria due to factors such as lack of immunity, delayed treatment, exposure to mosquitoes, and limited prevention efforts. Addressing these challenges is crucial for reducing malaria prevalence among this vulnerable population.

CONCLUSION

The study findings highlighted the need for targeted interventions to address the specific factors contributing to high malaria prevalence among seasonal migrant workers and to overcome the challenges in implementing effective malaria prevention strategies in this vulnerable population. Further study should be conducted to include the views and positions of seasonal migrant workers, owners of the farm areas, host communities, and political leaders.

Malaria prevalence and patients' knowledge, attitude, and preventive practices toward the disease in the Jawi District, Awi Zone, Northwest Ethiopia

Background

Malaria is the most important parasitic illness causing morbidity and mortality with high prevalence in tropical regions.

Objective

This study was aimed at evaluating the 7-year malaria trend and community awareness at Jawi Health Center and primary Hospital in Northwest Ethiopia.

Methods

A retrospective and cross-sectional or prospective design were used for the study. The data was analyzed using SPSS version 22 software. The findings were considered significant at P < 0.05.

Results

Among 62,624 blood films between 2015 and 2021 at Jawi Health Center, 40.9% were positive. Plasmodium falciparum accounted for 85.8%. Women had more mixed infections (P. falciparum and P. vivax) (X2 = 8.9, df = 2, P = 0.011) than men. A greater proportion (20.6%) of malaria cases was observed within the under 5 years age group and the number of malaria cases was higher in September, October, and June. The overall prevalence of malaria was found to be 25.2% and June had the highest proportion (75.6%). In total, 335 (80.9%) respondents recognized mosquito bites as the cause and fever (50%) as a clinical symptom of malaria. More than half of the respondents (60.1%) never sleep under mosquito nets.

Conclusion

Thus, these findings have substantial implications for the trend of malaria prevalence and patient awareness of the disease which support the existing malaria control efforts.

Waning success: a 2013-2022 spatial and temporal trend analysis of malaria in Ethiopia

BACKGROUND

Despite consecutive decades of success in reducing malaria transmission, Ethiopia went off track towards its goal of malaria elimination by 2030, as outlined in the NMCP malaria strategy. Recent malaria outbreaks in Ethiopia are attributed to the emergence and spread of diagnostic and drug-resistant Plasmodium falciparum, increased insecticide resistance in major vectors and the spread of invasive Anopheles stephensi. The effects of the COVID-19 pandemic, environmental anomalies and internal conflicts have also potentially played a role in increasing malaria transmission. This study aimed to evaluate the contribution of environmental factors and An. stephensi to the spatiotemporal trends of recent malaria cases in Ethiopia.

METHODS

Clinical malaria case data reported weekly between January 2013 and January 2023 were obtained from the Ethiopian Public Health Institute (EPHI), Addis Ababa. A negative binomial regression model was used to explain the variability and potential overdispersion in the weekly number of malaria cases reported across Ethiopian administrative zones. This model incorporated fixed effects for selected environmental factors and random effects to capture temporal trends, zone specific seasonal patterns, spatial trends at the zone level, and the presence of An. stephensi and its impact.

RESULTS

Our negative binomial regression model highlighted 56% variability in the data and slightly more than half (55%) was due to environmental factors, while the remainder was captured by random effects. A significant nationwide decline in malaria risk was observed between 2013 and 2018, followed by a sharp increase in early 2022. Malaria risk was higher in western and northwestern zones of Ethiopia compared to other zones. Zone-specific seasonal patterns, not explained by environmental factors, were grouped into four clusters of seasonal behaviours. The presence of An. stephensi was not shown to have any significant impact on malaria risk.

CONCLUSIONS

Understanding the spatial and temporal drivers of malaria transmission and therefore identifying more appropriate malaria control strategies are key to the success of any malaria elimination and eradication programmes in Ethiopia. Our study found that approximately 50% of malaria risk variability could be explained by environmental, temporal, and spatial factors included in the analysis, while the remaining variation was unexplained and may stem from other factors not considered in this study. This highlights the need for a better understanding of underlying factors driving local malaria transmission and outbreaks, to better tailor regional programmatic responses.

Impact of Climate Variability and Interventions on Malaria Incidence and Forecasting in Burkina Faso

BACKGROUND

Malaria remains a climate-driven public health issue in Burkina Faso, yet the interactions between climatic factors and malaria interventions across different zones are not well understood. This study estimates time delays in the effects of climatic factors on malaria incidence, develops forecasting models, and assesses their short-term forecasting performance across three distinct climatic zones: the Sahelian zone (hot/arid), the Sudano-Sahelian zone (moderate temperatures/rainfall); and the Sudanian zone (cooler/wet).

METHODS

Monthly confirmed malaria cases of children under five during the period 2015-2021 were analyzed using Bayesian generalized autoregressive moving average negative binomial models. The predictors included land surface temperature (LST), rainfall, the coverage of insecticide-treated net (ITN) use, and the coverage of artemisinin-based combination therapies (ACTs). Bayesian variable selection was used to identify the time delays between climatic suitability and malaria incidence. Wavelet analysis was conducted to understand better how fluctuations in climatic factors across different time scales and climatic zones affect malaria transmission dynamics.

RESULTS

Malaria incidence averaged 9.92 cases per 1000 persons per month from 2015 to 2021, with peak incidences in July and October in the cooler/wet zone and October in the other zones. Periodicities at 6-month and 12-month intervals were identified in malaria incidence and LST and at 12 months for rainfall from 2015 to 2021 in all climatic zones. Varying lag times in the effects of climatic factors were identified across the zones. The highest predictive power was observed at lead times of 3 months in the cooler/wet zone, followed by 2 months in the hot/arid and moderate zones. Forecasting accuracy, measured by the mean absolute percentage error (MAPE), varied across the zones: 28% in the cooler/wet zone, 53% in the moderate zone, and 45% in the hot/arid zone. ITNs were not statistically important in the hot/arid zone, while ACTs were not in the cooler/wet and moderate zones.

CONCLUSIONS

The interaction between climatic factors and interventions varied across zones, with the best forecasting performance in the cooler/wet zone. Zone-specific intervention planning and model development adjustments are essential for more efficient early-warning systems.

Assessing the impact of ecological, climatic, and socioeconomic factors on age-specific malaria incidence in India: a mixed-model approach using the Global Burden of Disease Study (2010-2019)

BACKGROUND

Malaria continues to be a critical public health concern in India, predominantly driven by complex interplays of ecological, climatic, and socioeconomic factors.

METHODS

This study aimed to assess the association between climatic variables (temperature and precipitation) and malaria incidence across India from 2010 to 2019, utilizing data from the Global Historical Weather and Climate Data for climate metrics and the Global Burden of Disease Study for malaria incidence rates. Generalized Linear Mixed Models (GLMMs) with a Poisson distribution were employed to analyze the data, adjusting for socio-economic status, as indexed by the Human Development Index (HDI).

RESULTS

The results indicated a declining trend in both the number of malaria cases and age-specific incidence rates (ASIR) over the study period. In 2010, India reported approximately 20.7 million cases with an ASIR of 1688.86 per 100,000 population, which significantly reduced to 9.8 million cases and an ASIR of 700.80 by 2019. High malaria incidence was consistently observed in the states of Jharkhand and Odisha, whereas Sikkim reported the lowest numbers. Statistical analysis identified significant associations between malaria incidence and both temperature deviations and precipitation levels, with variations also linked to HDI, suggesting better detection and reporting capabilities in more developed areas.

CONCLUSION

The study underscores the critical interactions between climatic variables and socio-economic factors in shaping the trends of malaria incidence across India. These findings highlight the necessity for adaptive, localized public health strategies that integrate environmental monitoring with socio-economic data to efficiently predict and manage malaria outbreaks.

Characterization of larval habitats of Anopheles (Nyssorhynchus) darlingi and associated species in malaria areas in western Brazilian Amazon

BACKGROUND

Anopheles darlingi is the most efficient vector of malaria parasites in the Neotropics. Nevertheless, the specificities of its larval habitats are still poorly known.

OBJECTIVES

Characterize permanent larval habitats, and population dynamics of An. darlingi and other potential vectors in relation to climate, physicochemical variables, insect fauna and malaria cases.

METHODS

A 14-month longitudinal study was conducted in Porto Velho, Rondônia, western Brazilian Amazon. Monthly, 21 permanent water bodies were sampled. Immature anophelines and associated fauna were collected, physicochemical characteristics, and climate variables were recorded and analyzed.

FINDINGS

Five types of habitats were identified: lagoon, stream, stream combined with lagoon, stream combined with dam, and fishpond. A total of 60,927 anophelines were collected. The most abundant species in all habitats were Anopheles braziliensis and An. darlingi. The highest density was found in the lagoon, while streams had the highest species richness. Abundance was higher during the transition period wet-dry season. There was a lag of respectively four and five months between the peak of rainfall and the Madeira River level and the highest abundance of An. darlingi larvae, which were positively correlated with habitats partially shaded, pH close to neutrality, increase dissolved oxygen and sulphates.

MAIN CONCLUSIONS

The present study provides data on key factors defining permanent larval habitats for the surveillance of An. darlingi and other potential vectors as well as a log-linear Negative Binomial model based on immature mosquito abundance and climate variables to predict the increase in the number of malaria cases.

Assessing the relationship between malaria incidence levels and meteorological factors using cluster-integrated regression

This paper introduces a novel approach to modeling malaria incidence in Nigeria by integrating clustering strategies with regression modeling and leveraging meteorological data. By decomposing the datasets into multiple subsets using clustering techniques, we increase the number of explanatory variables and elucidate the role of weather in predicting different ranges of incidence data. Our clustering-integrated regression models, accompanied by optimal barriers, provide insights into the complex relationship between malaria incidence and well-established influencing weather factors such as rainfall and temperature.We explore two models. The first model incorporates lagged incidence and individual-specific effects. The second model focuses solely on weather components. Selection of a model depends on decision-makers priorities. The model one is recommended for higher predictive accuracy. Moreover, our findings reveal significant variability in malaria incidence, specific to certain geographic clusters and beyond what can be explained by observed weather variables alone.Notably, rainfall and temperature exhibit varying marginal effects across incidence clusters, indicating their differential impact on malaria transmission. High rainfall correlates with lower incidence, possibly due to its role in flushing mosquito breeding sites. On the other hand, temperature could not predict high-incidence cases, suggesting that other factors other than temperature contribute to high cases.Our study addresses the demand for comprehensive modeling of malaria incidence, particularly in regions like Nigeria where the disease remains prevalent. By integrating clustering techniques with regression analysis, we offer a nuanced understanding of how predetermined weather factors influence malaria transmission. This approach aids public health authorities in implementing targeted interventions. Our research underscores the importance of considering local contextual factors in malaria control efforts and highlights the potential of weather-based forecasting for proactive disease management.

Relationship between the colours of the rivers in the Amazon and the incidence of malaria

BACKGROUND

Malaria is transmitted by different Anopheles species. In Brazil, the disease is concentrated in the Amazon region. Rivers play an important role in the life cycle of malaria since the vector reproduces in aquatic environments. The waters of the rivers in the Amazon have distinct chemical characteristics, which affect the colour of the water and therefore, the study analysed whether the colour of the waters of the rivers have an on influence the distribution of malaria. The goal of the study was to correlate the different colourations of the water (black, white and mixed water) and the malaria incidence in 50 municipalities of the Amazonas state, Brazil, and then test hypotheses about the characteristics of the colour of the rivers and disease incidence.

METHODS

This study was conducted for a period of seventeen years (2003-2019) in 50 municipalities in the state of Amazonas, Brazil. A conditionally Gaussian dynamic linear model was developed to analyse the association of malaria incidence and three types of river colour: white, black and mixed.

RESULTS

The analyses indicate that the distribution of malaria is related to the colouration of the rivers. The results showed that places located near black-water rivers have a higher malaria incidence when compared to places on the banks of white-water rivers.

CONCLUSIONS

Historically, the hydrological regime has played an important role in the dynamics of malaria in the Amazon, but little is known about the relationship between river colours and the incidence of the disease. This research was carried out in a region with hydrographic characteristics that were heterogeneous enough to allow an analysis that contrasted different colours of the rivers and covered almost the whole of the state of Amazonas. The results help to identify the places with the highest risk of malaria transmission and it is believed that they will be able to contribute to more precise planning of actions aimed at controlling the disease in the region.

Association between malaria and undernutrition among pregnant women at presentation for antenatal care in health facilities in the Mount Cameroon region

In resource limited settings, malaria and undernutrition are major public health problems in pregnancy. Therefore, this study assessed the association between malaria infection and undernutrition among pregnant women in the Mount Cameroon area. This cross-sectional study enrolled 1,014 pregnant women consecutively over a year. A structured questionnaire was used to collect socio-demographic information and clinical data. Maternal nutrition was assessed using dietary diversity (DD). Peripheral blood samples collected were used for the diagnosis of malaria parasitaemia by microscopy whereas haemoglobin (Hb) levels were determined using an Hb meter. Logistic regression was used to determine factors associated with malaria and dietary diversity. The prevalence of malaria infection and undernutrition was 17.8% and 89.6% respectively. In addition, of those infected with malaria, geometric mean parasite density was 301/μL of blood (range: 40-9280) while mean DD score was 3.57±0.82 (range: 1-7). The odds of being infected with malaria parasitaemia was highest among women enrolled in the rainy season (OR = 1.58, P = 0.043), who were farmers (OR = 2.3, P = 0.030), had a household size of < 4 individuals (OR = 1.48, P = 0.026) and who were febrile (OR = 1.87, P < 0.001). Also, attending clinic visits in Mutengene Medical Centre (OR = 2.0, P = 0.012) or Buea Integrated Health Centre (OR = 2.9, P = < 0.001), being < 25 years (OR = 2.4, P = 0.002) and a farmer (OR = 10.6, P = 0.024) as well as < 4 clinic visits (OR = 1.62, P = 0.039) were identified as predictors of undernutrition. Furthermore, the association between malaria and DD was statistically significant (P = 0.015). In this study, undernutrition was highly frequent than malaria infection. Thus, there is an urgent need to improve maternal awareness through nutritional counselling and health campaigns on the benefits of consuming at least five food groups. Besides, improved maternal dietary nutrient intake is likely to have impact on the burden of malaria parasite infection.

Climate change and malaria: some recent trends of malaria incidence rates and average annual temperature in selected sub-Saharan African countries from 2000 to 2018

BACKGROUND

Malaria is still a disease of massive burden in Africa, also influenced by climate change. The fluctuations and trends of the temperature and precipitation are well-known determinant factors influencing the disease's vectors and incidence rates. This study provides a concise account of malaria trends. It describes the association between average temperature and malaria incidence rates (IR) in nine sub-Saharan African countries: Nigeria, Ethiopia, South Africa, Kenya, Uganda, Ghana, Mozambique, Zambia and Zimbabwe. The incidence of malaria can vary both in areas where the disease is already present, and in regions where it is present in low numbers or absent. The increased vulnerability to the disease under increasing average temperatures and humidity is due to the new optimal level for vector breeding in areas where vector populations and transmission are low, and populations are sensitive due to low acquired immunity.

METHODS

A second source trend analysis was carried out of malaria cases and incidence rates (the number of new malaria cases per 1000 population at risk per year) with data from the World Health Organization (WHO) and average annual mean temperature from 2000 to 2018 from the World Bank's Climate Change Knowledge Portal (CCKP). Additionally, descriptive epidemiological methods were used to describe the development and trends in the selected countries. Furthermore, MS Excel was chosen for data analysis and visualization.

RESULTS

Findings obtained from this article align with the recent literature, highlighting a declining trend (20-80%) of malaria IR (incidence rate) from 2000 to 2018. However, malaria IR varies considerably, with high values in Uganda, Mozambique, Nigeria and Zambia, moderate values in Ghana, Zimbabwe, and Kenya, and low values in South Africa and Ethiopia in 2018. Evidence suggests varying IRs after average temperature fluctuations in several countries (e.g., Zimbabwe, Ethiopia). Also, an inverse temperature-IR relationship occurs, the sharp decrease of IR during 2012-2014 and 2000-2003, respectively, occurred with increasing average temperatures in Ghana and Nigeria. The decreasing trends and fluctuations, partly accompanying the temperature, should result from the intervention programmes and rainfall variability. The vulnerability and changing climate could arrest the recent trends of falling IR.

CONCLUSION

Thus, malaria is still a crucial public health issue in sub-Saharan Africa, although a robust decreasing IR occurred in most studied countries.

Burden and seasonal distribution of malaria in Ziquala district, Northeast Ethiopia: a 5-year multi-centre retrospective study

OBJECTIVE

This study was aimed to determine the 5-year trend of malaria positivity rate in Ziquala district, Northeast Ethiopia.

METHODS

Review of blood film reports from health institutions' laboratory record books using predesigned checklists was done as part of an institution-based retrospective study to assess the 5-year (2016/2017-2020/2021) trend of malaria. To display data and analyse patterns in the trend of malaria over the course of years, months and seasons, descriptive statistics were used. The results of the data analysis were displayed in tables and figures using SPSS V.26.0. P values under 0.05 were considered as statistically significant for all comparisons.

RESULTS

A total of 46 365 blood films from malaria suspected individuals were diagnosed using microscopy over the last 5 years. Of the diagnosed individuals, 14 429 (31.1%) were confirmed positive for Plasmodium infection. Plasmodium falciparum (59.7%) and Plasmodium vivax (37.0%) were the dominant species. The positivity rate of mixed infection (P. falciparum and P. vivax) was 3.3%. The maximum (3598; 29.6%) and minimum (2085; 29.1%) number of cases were reported in 2019/2020 and 2020/2021, respectively. Of the total cases, 9206 (63.8%) were in males. Moreover, the highest malaria positivity rate was observed in the age group of 15-45 (4040; 28.0%). Among the six health facilities, Ziquala district hospital had the highest malaria positivity rate (35.8%), followed by Tsitsika health centre (27.3%) and Mishra health centre (14.2%).

CONCLUSION

With P. falciparum being the most common species, malaria remains a severe public health threat in the district. Therefore, the district health office and other concerned bodies should strengthen and implement evidence-based malaria prevention and control measures.

Spatio-temporal analysis of malaria incidence and its risk factors in North Namibia

BACKGROUND

Millions of dollars have been spent in fighting malaria in Namibia. However, malaria remains a major public health concern in Namibia, mostly in Kavango West and East, Ohangwena and Zambezi region. The primary goal of this study was to fit a spatio-temporal model that profiles spatial variation in malaria risk areas and investigate possible associations between disease risk and environmental factors at the constituency level in highly risk northern regions of Namibia.

METHODS

Malaria data, climatic data, and population data were merged and Global spatial autocorrelation statistics (Moran's I) was used to detect the spatial autocorrelation of malaria cases while malaria occurrence clusters were identified using local Moran statistics. A hierarchical Bayesian CAR model (Besag, York and Mollie's model "BYM") known to be the best model for modelling the spatial and temporal effects was then fitted to examine climatic factors that might explain spatial/temporal variation of malaria infection in Namibia.

RESULTS

Average rainfall received on an annual basis and maximum temperature were found to have a significant spatial and temporal variation on malaria infection. Every mm increase in annual rainfall in a specific constituency in each year increases annual mean malaria cases by 0.6%, same to average maximum temperature. The posterior means of the time main effect (year t) showed a visible slightly increase in global trend from 2018 to 2020.

CONCLUSION

The study discovered that the spatial temporal model with both random and fixed effects best fit the model, which demonstrated a strong spatial and temporal heterogeneity distribution of malaria cases (spatial pattern) with high risk in most of the Kavango West and East outskirt constituencies, posterior relative risk (RR: 1.57 to 1.78).

The synergistic effect of climatic factors on malaria transmission: a predictive approach for northeastern states of India

The northeast region of India is highlighted as the most vulnerable region for malaria. This study attempts to explore the epidemiological profile and quantify the climate-induced influence on malaria cases in the context of tropical states, taking Meghalaya and Tripura as study areas. Monthly malaria cases and meteorological data from 2011 to 2018 and 2013 to 2019 were collected from the states of Meghalaya and Tripura, respectively. The nonlinear associations between individual and synergistic effect of meteorological factors and malaria cases were assessed, and climate-based malaria prediction models were developed using the generalized additive model (GAM) with Gaussian distribution. During the study period, a total of 216,943 and 125,926 cases were recorded in Meghalaya and Tripura, respectively, and majority of the cases occurred due to the infection of Plasmodium falciparum in both the states. The temperature and relative humidity in Meghalaya and temperature, rainfall, relative humidity, and soil moisture in Tripura showed a significant nonlinear effect on malaria; moreover, the synergistic effects of temperature and relative humidity (SI=2.37, RERI=0.58, AP=0.29) and temperature and rainfall (SI=6.09, RERI=2.25, AP=0.61) were found to be the key determinants of malaria transmission in Meghalaya and Tripura, respectively. The developed climate-based malaria prediction models are able to predict the malaria cases accurately in both Meghalaya (RMSE: 0.0889; R²: 0.944) and Tripura (RMSE: 0.0451; R²: 0.884). The study found that not only the individual climatic factors can significantly increase the risk of malaria transmission but also the synergistic effects of climatic factors can drive the malaria transmission multifold. This reminds the policymakers to pay attention to the control of malaria in situations with high temperature and relative humidity and high temperature and rainfall in Meghalaya and Tripura, respectively.

Seasonal and spatial variations of malaria transmissions in northwest Ethiopia: Evaluating climate and environmental effects using generalized additive model

The impacts of climate change and environmental predictors on malaria epidemiology remain unclear and not well investigated in the Sub-Sahara African region. This study was aimed to investigate the nonlinear effects of climate and environmental factors on monthly malaria cases in northwest Ethiopia, considering space-time interaction effects. The monthly malaria cases and populations sizes of the 152 districts were obtained from the Amhara public health institute and the central statistical agency of Ethiopia. The climate and environmental data were retrieved from US National Oceanic and Atmospheric Administration. The data were analyzed using a spatiotemporal generalized additive model. The spatial, temporal, and space-time interaction effects had higher contributions in explaining the spatiotemporal distribution of malaria transmissions. Malaria transmission was seasonal, in which a higher number of cases occurred from September to November. The long-term trend of malaria incidence has decreased between 2012 and 2018 and has turned to an increased pattern since 2019. Areas neighborhood to the Abay gorge and Benshangul-Gumuz, South Sudan, and Sudan border have higher spatial effects. Climate and environmental predictors had significant nonlinear effects, in which their effects are not stationary through the ranges of values of variables, and they had a smaller contributions in explaining the variabilities of malaria incidence compared to seasonal, spatial and temporal effects. Effects of climate and environmental predictors were nonlinear and varied across areas, ecology, and landscape of the study sites, which had little contribution to explaining malaria transmission variabilities with an account of space and time dimensions. Hence, exploring and developing an early warning system that predicts the outbreak of malaria transmission would have an essential role in controlling, preventing, and eliminating malaria in areas with lower and higher transmission levels and ultimately lead to the achievement of malaria GTS milestones.

A Retrospective Study on the Burden of Malaria in Northeastern Ethiopia from 2015 to 2020: Implications for Pandemic Preparedness

Background

Regardless of various prevention and control strategies, malaria continues to be a significant public health problem in Ethiopia. As there are few studies on malaria trend analysis in Northeastern Ethiopia, it hinders the evaluation of ongoing and prioritization of new malaria intervention strategies, particularly during the period of pandemics. Therefore, the present study investigated the trend of malaria prevalence in Northeastern Ethiopia from 2015 to 2020.

Methods

An institution-based retrospective study was employed to assess the trend of malaria prevalence over a 6-year period (2015-2020) in three districts (Jile tumuga, Aruma fursi, and Dawachefa) of Northeastern Ethiopia. Data were extracted from clinical records of malaria cases by trained medical laboratory technologists. The associations between the prevalence of malaria and independent variables (age group, malaria transmission season, and districts) were assessed using chi-square test. P-values with a cut-off point of 0.05 were used to determine statistically significant associations.

Results

In our study area, a total of 212,952 malaria suspected patients were diagnosed over the 6 years. Of these, 33,005 (15.5%) were confirmed malaria cases. The identified Plasmodium species were Plasmodium falciparum and P. vivax, accounting for 66.4% and 33.6%, respectively. These with the age of >15 years old were the most affected (41.9%). The highest numbers of malaria cases (34.6%) were recorded during spring season (September to November). The prevalence of Plasmodium species showed a significant association with age (X²=9.7; p=0.002), districts (X²=13.5; p<0.001), and malaria transmission season (X²=16.5; p<0.001).

Conclusion

In our study area, P. falciparum is the dominant species. We noted that malaria remains a public health concern and fluctuates throughout the years. Therefore, national, regional, zonal, and district health bureaus should strengthen the ongoing and devise appropriate prevention and control strategies even during the period of pandemics.

Prevalence of asymptomatic malaria and associated factors among pregnant women at Boset District in East Shoa Zone, Oromia Region, Ethiopia: a cross-sectional study

BACKGROUND

Malaria infection during pregnancy is a significant public health problem that puts pregnant women at risk. Interruption of transmission of asymptomatic malaria among a population remained a challenge and the host serves as a reservoir for the malaria parasite; and is also recognized as a major barrier to malaria elimination. This study aimed to assess the prevalence of asymptomatic malaria and associated factors among pregnant women in the Boset District, East Shoa Zone, Oromia, Ethiopia.

METHODS

A community-based cross-sectional study was conducted to assess the prevalence of asymptomatic malaria and associated factors in pregnant women from February to March 2022. Using multistage sample techniques, 328 asymptomatic pregnant women were enrolled. Data were collected using a structured questionnaire. A rapid test and Giemsa-stained blood smear microscopy were used to diagnose Plasmodium infections. Epi info version 7 was used to code, enter, and clean data before being uploaded to SPSS version 25.0 for analysis. Bivariable and multivariable binary logistic regression were employed to find the associated factors. Variables in the multivariable model with a p-value < 0.05 were considered significantly associated with asymptomatic malaria.

RESULTS

Of the total 328 pregnant women who participated in this study, 9(2.74%) and 10(3.05%) were confirmed to be infected with Plasmodium species by microscopy and rapid diagnostic tests, respectively. Asymptomatic malaria during pregnancy was found to be significantly associated with not using an insecticide-treated bed net [(P = 0.002, AOR: 9.61; 95% CI (2.22-41.53)], lack of consultation and health education about malaria prevention during Antenatal care attendance [(P = 0.04, AOR: 4.05; 95% CI (1.02, 16.05)], and living close stagnant water [(P = 0.02, AOR: 4.43; 95% CI (1.17,16.82)].

CONCLUSIONS

The current study showed that asymptomatic malaria is prevalent in pregnant women. Not using insecticide-treated bed nets, inadequate health education during antenatal care, and living close to stagnant water are significantly associated with malaria infection. Thus, using insecticide-treated bed nets, health education, and avoiding stagnant water from residential areas could play significant roles in preventing asymptomatic malaria among pregnant women in the study area.

Species diversity pattern of mosquitoes (Diptera: Culicidae) breeding in different permanent, temporary and natural container habitats of Peshawar, KP Pakistan

To determine the species composition, relative abundance and seasonal variation of different mosquitoes Genera (Aedes, Anopheles, Armigeres, Culex, and Culiseta) in different habitats the present research work was carried out in Entomology Research Laboratory of The University of Peshawar. Sampling performed from variety of permanent and temporary breeding habitats was carried out on monthly basis from targeted breeding sites for two consecutive years through dipping method. Species diversity in the survey sites was noted. Collection from these seventeen various types of potential larval habitats, yielded a total of 42,430 immature constituting 41,556 larvae and 874 pupae. Among these only 19,651 adult mosquitoes emerged comprising 11,512 female and 8,139 male mosquitoes. 78% (n= 15333) of mosquito larvae were from permanent and 22% (n=4318) were from temporary breeding sites. This study showed that Peshawar valley harbours 15 species from the genera Aedes, Anopheles, Armigeres, Culex and Culiseta. When the density of each species was examined, Culex quinquifasciatus was found to be dominant (79%) and constant in distribution. Among the temporary habitats Aedes albopictus was found as the most prevalent species particularly from tree holes and water cisterns. The highest intensity of mosquitoes was in June (2243 emerged adults) and November (2667 emerged adults) while the lowest was in January (203 emerged adults). A perfect positive correlation (r = +0.8) was found between temperature and population of mosquitoes (df 10 and α 0.05). The species diversity index for mosquitoes remained between 0.12 and 1.76. The Margalef's richness components was noticeably low for bamboo traps (0.2) and fairly high for rice fields, Percolating water and Animal tracks (1.3) which shows the abundance of mosquito species in these habitats. Similarly Pielou's Evenness was highest for bamboo traps (E=1) showing species uniform distribution. Animal tracks were presumed not only the diverse habitat rather also possessed high value for species richness and species evenness. Temperature, rainfall, humidity and other related attributes responsible for species variation and abundance need to be analysed further to pave way for controlling vector species in their oviposition targeted sites.

Optimization of soluble phosphate and IAA production using response surface methodology and ANN approach

Phosphorus (P) is often found inaccessible to plants, as it forms precipitates with cations and can be converted to accessible forms by using Phosphate solubilizing bacteria (PSB). In the present study, isolation and characterization of PSB from rhizospheric soil of coffee plants were performed. The influence of four independent variables (incubation temperature, incubation time, pH, and inoculum size) was investigated and optimized using an artificial neural network and response surface methodology on the solubility of phosphate and indole acetic acid production. The bacterium that can dissolve phosphate were isolated in Pikovskaya's agar containing insoluble tricalcium phosphate. Total, six Phosphate Solubilizing Bacteria were isolated and three of them (PSB1, PSB3, and PSB4) were found to be effectively solubilizing phosphate. Based on phosphate solubilizing index results Pseudomonas bacteria (PSB1) was selected for modeling. The results showed that both models performed reasonably well, but properly trained artificial neural networks have the more powerful modeling capability compared to the response surface method. The optimum conditions were found to be incubation temperature of 37.5 °C, incubation time of 9 days, pH of 7.2, and inoculum size of 1.89 OD. Under these conditions, the model predicted solubility of phosphate of 260.69 μg/ml and production of IAA of 80.00 μg/ml with a desirability value of 0.947. In general, the isolated Pseudomonas is expected to have phosphorus-degrading ability that promotes plant growth, and further field experimental work is required to use this bacterial strain as biofertilizer, as an alternative to synthetic fertilizer.

Projecting Malaria Incidence Based on Climate Change Modeling Approach: A Systematic Review

BACKGROUND: Climate change will affect the transmission of malaria by shifting the geographical space of the vector. AIM: The review aims to examine the climate change modeling approach and climatic variables used for malaria projection. METHODS: Articles were systematically searched from four databases, Scopus, Web of Science, PubMed, and SAGE. The PICO concept was used for formulation search and PRISMA approach to identify the final articles. RESULTS: A total of 27 articles were retrieved and reviewed. There were six climate factors identified in this review: Temperature, rainfall/precipitation, humidity, wind, solar radiation, and climate change scenarios. Modeling approaches used to project future malarial trend includes mathematical and computational approach. CONCLUSION: This review provides robust evidence of an association between the impact of climate change and malaria incidence. Prediction on seasonal patterns would be useful for malaria surveillance in public health prevention and mitigation strategies.

An investigation of the efficacy of different statistical models in malaria forecasting in the semi-arid regions of Gujarat, India

BACKGROUND & OBJECTIVES

Robust forecasting of malaria cases is desirable as we are approaching towards malaria elimination in India. Methods enabling robust forecasting and timely case detection in unstable transmission areas are the need of the hour.

METHODS

Forecasting efficacy of the eight most prominent statistical models that are based on three statistical methods: Generalized linear model (Model A and Model B), Smoothing method (Model C), and SARIMA (Model D to model H) were compared using last twelve years (2008-19) monthly malaria data of two districts (Kheda and Anand) of Gujarat state of India.

RESULTS

The SARIMA Model F was found the most appropriate when forecasted for 2017 and 2018 using model-building data sets 1 and 2, respectively, for both the districts: Kheda and Anand. Model H followed by model C were the two models found appropriate in terms of point estimates for 2019. Still, we regretted these two because confidence intervals from these models are wider that they do not have any forecasting utility. Model F is the third one in terms of point prediction but gives a relatively better confidence interval. Therefore, model F was considered the most appropriate for the year 2019 for both districts.

INTERPRETATION & CONCLUSION

Model F was found relatively more appropriate than others and can be used to forecast malaria cases in both districts.

Repellent activity against Anopheles gambiae of the leaves of nesting trees in the Sebitoli chimpanzee community of Kibale National Park, Uganda

BACKGROUND

Every evening, chimpanzees (Pan troglodytes) build a sleeping platform so called "nest" by intertwining branches of tree. Most of chimpanzees' communities studied have a preference for tree species in which they nest. As female mosquitoes are feeding on the blood of their host at nighttime, chimpanzees may prevent being disturbed and bitten by mosquitoes by selecting tree species having properties to repel them.

METHODS

To test the hypothesis that chimpanzees choose tree species for their aromatic properties, data related to 1,081 nesting trees built between 2017 and 2019 in the Sebitoli community of Kibale National Park (Uganda) were analysed. The 10 most used trees were compared to the 10 most common trees in the habitat that were not preferred for nesting. Leaves from the 20 trees species were collected and hydro-distillated to obtain essential oils and one of the by-products for behavioural bioassays against females of the African mosquito, Anopheles gambiae.

RESULTS

Sebitoli chimpanzees showed tree preferences: 10 species correspond to more than 80% of the nesting trees. Out of the essential oil obtained from the 10 nesting trees, 7 extracts for at least one concentration tested showed spatial repellency, 7 were irritant by contact and none were toxic. In the other hand, for the abundant trees in their habitat not used by chimpanzees, only 3 were repellent and 5 irritants.

DISCUSSION AND CONCLUSION

This study contributes to evidence that chimpanzees, to avoid annoying mosquitoes, may select their nesting trees according to their repellent properties (linked to chemical parameters), a potential inspiration for human health.

Milk composition, traditional processing, marketing, and consumption among smallholder dairy farmers in selected towns of Jimma Zone, Oromia Regional State, Ethiopia

In Ethiopia, dairy products remain the most important animal source of foods including in the current study area. However, poor milk quality is frequently told constraint, and this affects smallholder dairy development. This study aimed to assess raw cow milk composition, processing, consumption, and marketing among smallholder dairy producers in selected towns of Jimma Zone, Ethiopia. Primary data were collected by surveying 52 randomly selected dairy cattle keeping households using a structured questionnaire and analysis of raw milk chemical composition. The results revealed that the average milk production was 5.98 ± 1.01 liters/household/day, of which the majority (62.9%) was marketed. About 22.7% of households reported processing milk into butter, cottage cheese, ghee, and fermented milk at household level mainly for domestic use. A combination of fresh whole milk, fermented milk, butter, cottage cheese, and ghee (51.7%) were the main dairy products consumed by respondents. About 72.2% and 6.1% of households consumed boiled and raw milk, respectively, while 100% respondents reported consuming raw fermented whole milk. Milk was channeled to consumers and retailers through informal marketing system (100%). The awareness of respondents about zoonotic diseases was found to be very low. The mean fat, lactose, and protein content of raw cow milk were significantly (p < .05) affected by breed. It is recommended that consumption of raw milk and fermented milk could pose a public health risk to consumers, implying the need for urgent farmers' awareness creation to boil milk before consumption for prevention and control of zoonotic diseases.

Predicting malaria outbreaks from sea surface temperature variability up to 9 months ahead in Limpopo, South Africa, using machine learning

Malaria is the cause of nearly half a million deaths worldwide each year, posing a great socioeconomic burden. Despite recent progress in understanding the influence of climate on malaria infection rates, climatic sources of predictability remain poorly understood and underexploited. Local weather variability alone provides predictive power at short lead times of 1-2 months, too short to adequately plan intervention measures. Here, we show that tropical climatic variability and associated sea surface temperature over the Pacific and Indian Oceans are valuable for predicting malaria in Limpopo, South Africa, up to three seasons ahead. Climatic precursors of malaria outbreaks are first identified via lag-regression analysis of climate data obtained from reanalysis and observational datasets with respect to the monthly malaria case count data provided from 1998-2020 by the Malaria Institute in Tzaneen, South Africa. Out of 11 sea surface temperature sectors analyzed, two regions, the Indian Ocean and western Pacific Ocean regions, emerge as the most robust precursors. The predictive value of these precursors is demonstrated by training a suite of machine-learning classification models to predict whether malaria case counts are above or below the median historical levels and assessing their skills in providing early warning predictions of malaria incidence with lead times ranging from 1 month to a year. Through the development of this prediction system, we find that past information about SST over the western Pacific Ocean offers impressive prediction skills (~80% accuracy) for up to three seasons (9 months) ahead. SST variability over the tropical Indian Ocean is also found to provide good skills up to two seasons (6 months) ahead. This outcome represents an extension of the effective prediction lead time by about one to two seasons compared to previous prediction systems that were more computationally costly compared to the machine learning techniques used in the current study. It also demonstrates the value of climatic information and the prediction framework developed herein for the early planning of interventions against malaria outbreaks.

Malaria Infection, Parasitemia, and Hemoglobin Levels in Febrile Patients Attending Sibu Sire Health Facilities, Western Ethiopia

Background

Malaria is endemic in tropical and subtropical regions and causes up to one million deaths each year. It mostly affects sub-Saharan African countries including Ethiopia. In Ethiopia, it was estimated that about 75% of the land and 68% of the population are exposed to malaria. The aim of the current study was to determine malaria cases, its impact on the level of hemoglobin, and parasitemia and predisposing factors among febrile patients who visited Sibu Sire Health Care centers.

Methods

Institution-based cross-sectional study was undertaken from May to October, 2020. Febrile patients who visited Sibu Sire Health Care centers were purposefully selected as the target population for the present study. Blood samples were collected and thick and thin smears stained with Giemsa. Hemoglobin level was determined using HemoCue Hb 301. Structured questionnaire and SPSS statistical software were used to collect and analyze data. P value < 0.05 was stated as statistically significant.

Results

The overall prevalence of malaria was 168/979 (17.2%) out of which Plasmodium falciparum was 132/168 (78.5%), Plasmodium vivax was 27/168 (16.1%), and mixed infection was 9/168 (5.4%). To assess factors associated with dependent variable and determine the strength of association, binary logistic regression was used at adjusted odds ratios with 95% confidence intervals. The associations between malaria cases, hemoglobin levels, and parasitemia were estimated to evaluate the impacts of malaria on hemoglobin levels and parasitemia level. Out of 979 febrile patients (male 453 and female 526), 168 (male 99 and female 69) individuals were infected with Plasmodium species and Plasmodium falciparum were the predominant parasites. The majority of the study participants 144/168 (85.7%) were from rural residences. Highest malaria-infected patients 74/168 (44%) were aged between 15 and 30 years old. The level of hemoglobin and parasitemia was highly associated with malaria cases; hence, in this study area, intensities of hemoglobin and parasitemia are significantly associated with Plasmodium species.

Conclusion

There was a moderate prevalence of malaria parasitemia and hemoglobin level among patients visiting Sibu Sire Health Care center; however, it needs further intervention to prevent and control malaria transmission in this malaria hotspot area.

Malaria Transmission and Vector Resistance to Insecticides in a Changing Environment: Case of Simbock in Yaoundé-City, Cameroon

Ecological upheavals resulting from uncontrolled urbanization can lead to significant changes in vector borne diseases’ profiles, thus requiring a thorough revision of their prevention and control strategies. The current study aimed at characterizing malaria vector populations in the Simbock neighborhood of Yaoundé-city (Cameroon), in relation to its urbanization scheme. Adult mosquitoes were captured by human landing catches (HLC) in- and outdoors prior to (2000–2006) and during infrastructural development (2014–2016). Anophelines were morphologically identified and analyzed for Plasmodium (P.) falciparum circumsporozoite protein detection using the ELISA technique. Species of the Anopheles (An.) gambiae complex were identified using SINE-PCR. Adult An. gambiae s.l. from larvae collected between 2014 and 2017 were tested for susceptibility to insecticides (0.1% bendiocarb, 4% DDT, 0.75% permethrin and 0.05% deltamethrin) with or without piperonyl butoxide (PBO) synergist, using WHO standard bioassays. The Hot Oligonucleotide Ligation Assay was used to detect the knockdown resistance (kdr) L995F/S mutations. Overall, nine malaria vector species were identified in 2000-2006, mostly An. moucheti (49%), An. nili (13.5%) and An. gambiae s.l. (12%); the six remaining species were represented at less than 3% each. However, only three species were found in 2014-2016, with increasing proportions of An. gambiae s.l. (67%) and An. funestus (32%) (P&lt;0.0001). An. gambiae s.l. consisted An. coluzzii (&gt; 85%) and An. gambiae (&lt;15%) species during the two study periods. Plasmodium falciparum infection rates were 2.1% and 1.0% in 2000-2006 and 2014-2016 respectively (P=0.4), with decreasing entomological inoculation rates (EIR) from 0.34 infective bites per man per night (ib/m/n) to 0.02 ib/m/n (P&lt;0.0001). Anopheles gambiae s.l. was resistant to DDT and permethrin [&lt;40% mortality rates (MR)], and deltamethrin (65-89% MR), but fully susceptible to bendiocarb (100% MR). Pre-exposure of mosquitoes to PBO resulted in 90-100% MR to deltamethrin but not to permethrin. Furthermore, the two kdr L995F/S resistance alleles were recorded at 0.64 and 0.006 frequencies respectively. This study highlights a shift from rural to urban malaria transmission in Simbock, coupled with DDT and pyrethroid resistance in An. gambiae s.l. Combination vector control interventions, e.g., PBO nets and bendiocarb indoor residual spraying are needed in such areas.

Spatio-Temporal Variation of Malaria Incidence and Risk Factors in West Gojjam Zone, Northwest Ethiopia

Introduction

Malaria is a life-threatening acute febrile illness which is affecting the lives of millions globally. Its distribution is characterized by spatial, temporal, and spatiotemporal heterogeneity. Detection of the space-time distribution and mapping high-risk areas is useful to target hot spots for effective intervention.

Methods

Time series cross sectional study was conducted using weekly malaria surveillance data obtained from Amhara Public Health Institute. Poisson model was fitted to determine the purely spatial, temporal, and space-time clusters using SaTScan™ 9.6 software. Spearman correlation, bivariate, and multivariable negative binomial regressions were used to analyze the relation of the climatic factors to count of malaria incidence.

Result

Jabitenan, Quarit, Sekela, Bure, and Wonberma were high rate spatial cluster of malaria incidence hierarchically. Spatiotemporal clusters were detected. A temporal scan statistic identified 1 risk period from 1 July 2013 to 30 June 2015. The adjusted incidence rate ratio showed that monthly average temperature and monthly average rainfall were independent predictors for malaria incidence at all lag-months. Monthly average relative humidity was significant at 2 months lag.

Conclusion

Malaria incidence had spatial, temporal, spatiotemporal variability in West Gojjam zone. Mean monthly temperature and rainfall were directly and negatively associated to count of malaria incidence respectively. Considering these space-time variations and risk factors (temperature and rainfall) would be useful for the prevention and control and ultimately achieve elimination.

Hydrological Scenarios and Malaria Incidence in the Amazonian Context

In Brazil, approximately 99% of malaria cases are concentrated in the Amazon region. An acute febrile infectious disease, malaria is closely related to climatic and hydrological factors. Environmental variables such as rainfall, flow, level, and color of rivers, the latter associated with the suspended sediment concentration, are important factors that can affect the dynamics of the incidence of some infectious diseases, including malaria. This study explores the possibility that malaria incidence is influenced by precipitation, fluctuations in river levels, and suspended sediment concentration. The four studied municipalities are located in two Brazilian states (Amazonas and Pará) on the banks of rivers with different hydrological characteristics. The results suggest that precipitation and river level fluctuations modulate the seasonal pattern of the disease and evidence the existence of delayed effects of river floods on malaria incidence. The seasonality of the disease has a different influence in each municipality studied. However, municipalities close to rivers with the same characteristic color of waters (as a function of the concentration of suspended sediments) have similar responses to the disease.

Prevalence and Associated Factors of Malaria Infection among Outpatients Visiting Shewa Robit Health Center, Northcentral Ethiopia

Introduction

Malaria infection is a serious health problem killing millions in tropical developing countries including Ethiopia. The present study focused on assessing malaria prevalence and identification of determinants in Shewa Robit, northcentral Ethiopia.

Methods

A cross-sectional study was conducted among 422 participants who visited Shewa Robit Health Center between 01/10/2017 and 30/04/2018, using a simple random sampling. Sociodemographic characteristics were recorded using a pre-tested semi-structured questionnaire and infection was confirmed by microscopic examination. Data were analyzed using the Statistical Program for Social Sciences (SPSS) version 20 and p < 0.05 was used to indicate the level of significance.

Results

Eighty-one (19.0%) microscopically confirmed malaria cases were recorded, P.vivax was the most frequently detected species (n = 58; 71.6%). Interestingly, 73.2% (n = 309) of the participant did not utilize LLINs due to the fear of toxicity (37.4%, n = 158), misconception (21.6%, n = 91), and shortage (14.2%, n = 60). The data showed age, gender, marital status, family size, usage of LLINs and application of IRS, proximity to mosquito breeding sites and less robust and porous walls were the determinants of the infection in the study area.

Conclusion

The prevalence of malaria in the study population was high and P. vivax being the most common causative agent. Environmental and behavioral factors related to LLIN are the potential determinants of malaria. Continued public health interventions, targeting proper utilization of bed nets, drainage of stagnant water, and improved public awareness about reducing the risk of insect bites have the potential to minimize the infection.

Parous rate and longevity of anophelines mosquitoes in bure district, northwestern Ethiopia

The intensity of malaria transmission is measured by parous rate, daily survival rate, human blood meal frequency, sporozoite rate, and entomological inoculation rates. Female parous status is a key index of vector competence, adult vector longevity, recruitment rate of adult, and the length of a gonotrophic cycle. Hence, the present study was aimed to investigate the parous rate and the longevity of Anopheles mosquitoes in Bure District, Northwestern Ethiopia. Parous rate was estimated as the number of mosquitoes with parous ovaries divided by the number of females dissected multiplied by 100. Mosquito life expectancy (longevity as d) was estimated by. One way- ANOVA was applied to confirm the presence of parous rate difference in the villages (p < 0.05). A total of 952 unfed hosts-seeking Anopheles mosquitoes was dissected for parous rate determination. The overall parous rate of An. arabiensis in the district was 52.0%, and the highest parous rate was recorded in Shnebekuma than other villages (F 2, 33 = 6.974; p = 0.003). Similarly, the parous rate of An. cinereus showed significant variation among villages (F 2, 33 = 5.044, p = 0.012) and the highest rate (63.0%) was recorded in Bukta. The mean longevity of An. funestus, An. arabiensis, An. coustani, An. squamosus, An. pharoensis, and An. cinereus was 6.5 days, 4.6 days, 3.5 days, 3.7 days, 2.7 days, and 2.2 days, respectively. The longevity of each species was not sufficient to complete the life cycle of malaria parasite for malaria transmission throughout the year because P. falciparum requires from 12–14 day.

Liver Enzymes and Lipid Profile of Malaria Patients Before and After Antimalarial Drug Treatment at Dembia Primary Hospital and Teda Health Center, Northwest, Ethiopia

Background

Methods

Results

Conclusion

Burden of malaria, impact of interventions and climate variability in Western Ethiopia: an area with large irrigation based farming

Background

Land use change has increasingly been expanding throughout the world in the past decades. It can have profound effects on the spatial and temporal distribution of vector borne diseases like malaria through ecological and habitat change. Understanding malaria disease occurrence and the impact of prevention interventions under this intense environmental modification is important for effective and efficient malaria control strategy.

Methods

A descriptive ecological study was conducted by reviewing health service records at Abobo district health office. The records were reviewed to extract data on malaria morbidity, mortality, and prevention and control methods. Moreover, Meteorological data were obtained from Gambella region Meteorology Service Center and National Meteorology Authority head office. Univariate, bivariate and multivariate analysis techniques were used to analyze the data.

Results

For the twelve-year time period, the mean annual total malaria case count in the district was 7369.58. The peak monthly malaria incidence was about 57 cases per 1000 people. Only in 2009 and 2015 that zero death due to malaria was recorded over the past 12 years. Fluctuating pattern of impatient malaria cases occurrence was seen over the past twelve years with an average number of 225.5 inpatient cases. The data showed that there is a high burden of malaria in the district. Plasmodium falciparum (Pf) was a predominant parasite species in the district with the maximum percentage of about 90. There was no statistically significant association between season and total malaria case number (F_3,8: 1.982, P:0.195). However, the inter-annual total case count difference was statistically significant (F_11,132: 36.305, p < 0001). Total malaria case count had shown two months lagged carry on effect. Moreover, 3 months lagged humidity had significant positive effect on total malaria cases. Malaria prevention interventions and meteorological factors showed statistically significant association with total malaria cases.

Conclusion

Malaria was and will remain to be a major public health problem in the area. The social and economic impact of the disease on the local community is clearly pronounced as it is the leading cause of health facility visit and admission including the mortality associated with it. Scale up of effective interventions is quite important. Continuous monitoring of the performance of the vector control tools needs to be done.

Six-year trend analysis of malaria prevalence at University of Gondar Specialized Referral Hospital, Northwest Ethiopia, from 2014 to 2019

Globally, malaria is the major public health disease caused by plasmodium species and transmitted by the bite of the female anopheles mosquito. Assessment of the trend of malaria prevalence is important in the control and prevention of the disease. Therefore, the objective of this study was to assess the six year trend of malaria prevalence at the University of Gondar Comprehensive Specialized Hospital, northwest Ethiopia, from 2014 to 2019. A retrospective laboratory registration logbook review study was conducted on the malaria blood film examination results at the University of Gondar Comprehensive Specialized Hospital. The data was collected by using a data extraction tool and entered into SPSS version 20 for analysis. Descriptive statistics were used to summarize the socio-demographic characteristics of study participants and presented by graphs, tables and texts. The binary logistic regression was also used to test the association the trend of malaria prevalence and different factors like sex, age, year, and season. From a total of 17,500 malaria blood film examinations, 1341 (7.7%) were confirmed for malaria parasites. Of the confirmed malaria cases, 47.2%, 45.6% and 7.2% were P. vivax, P. falciparum and mixed infection, respectively. The proportion of P. vivax was the predominant species in the first three study years (2014-2016) and P. falciparum became the predominant species in the last three study years (2017-2019). The odds of malaria prevalence was lower by 68%, 60% and 69% in the year 2017, 2018 and 2019 compared to 2014, respectively. It was also 1.41 times higher in males than in females. Moreover, the odds of malaria prevalence were 1.60, 1.64, 2.45 and 1.82 times higher in the age group of < 5, 5-14, 15-24 and 25-54 years old compared to the older age groups (> 54 years old), respectively. Even there was a significant declining in prevalence trend; malaria is still a major public health problem. The study showed that there was high seasonal fluctuation from year to year. Moreover, males and the younger age groups were more affected than females and old age groups, respectively. Therefore, malaria prevention and control activities should be strengthened and require extra efforts by considering these variability.

Five-Year Trend Analysis of Malaria Cases in East Shawa Zone, Ethiopia

BACKGROUND

Malaria is an infectious disease caused by Plasmodium parasites. Of the five human malaria parasites Plasmodium falciparum and Plasmodium vivax are the two co-endemic predominant and widely distributed species in Ethiopia, with major public health importance. Even though enormous effort has been made countrywide to reduce the disease burden little was reported about trends of malaria transmission in the several localities of malarious areas like East Shawa Zone, Ethiopia. Thus, the present study was aimed at assessing fiveyear (2016-2020) trends of malaria transmission at Adama, Boset and Lume districts of East Shawa Zone of Oromia Regional State, Ethiopia.

METHODS

Retrospective data was extracted from the central surveillance database of East Shawa Zone Health Office. The data collected was analyzed from September 2020 to December 2020 to examine trends of malaria epidemiology in three malarious districts in the Zone.

RESULTS

The results of the present study showed a remarkable decrease in slide positivity rate (SPR) from 16.3 to 1.4% from 2016 to 2018 in the areas. However, a recent slight increase of malaria SPR was observed. On the other hand, as age increases more male individuals were infected with malaria compared to female of similar age groups. Falciparum, vivax and mixed malaria infection accounted for 53%, 41% and 6% respectively.

CONCLUSIONS

Even though, an overall reduction of malaria incidence was revealed in the study areas, an increase in malaria SPR was observed in 2019 and 2020. Such inconsistency in reduction of malaria cases in the study area demands due attention of health planners.

Malaria prevalence and associated risk factors in Dembiya district, North-western Ethiopia

Background

Ethiopia embarked on combating malaria with an aim to eliminate malaria from low transmission districts by 2030. A continuous monitoring of malaria prevalence in areas under elimination settings is important to evaluate the status of malaria transmission and the effectiveness of the currently existing malaria intervention strategies. The aim of this study was to assess the prevalence of malaria and associated risk factors in selected areas of Dembiya district.

Methods

A cross-sectional parasitological and retrospective survey was conducted in the two localities of Dembiya District, selected based on their long standing history of implementing malaria prevention and elimination strategies. Thin and thick blood smears collected from 735 randomly selected individuals between October and December, 2018 were microscopically examined for malaria parasites. Six years (2012–2017) retrospective malaria data was collected from the medical records of the health centres. Structured questionnaires were prepared to collect information about the socio-economic data of the population. Logistic regression analysis was used to determine a key risk factor explaining the prevalence of malaria. The data were analysed using SPSS version 20 and p ≤ 0.05 were considered statistically significant.

Results

The 6-year retrospective malaria prevalence trend indicates an overall malaria prevalence of 22.4%, out of which Plasmodium falciparum was the dominant species. From a total of 735 slides examined for the presence of malaria parasites, 3.5% (n = 26) were positive for malaria parasites, in which P. falciparum was more prevalent (n = 17; 2.3%), Plasmodium vivax (n = 5; 0.7%), and mixed infections (n = 4; 0.5%). Males were 2.6 times more likely to be infected with malaria than females (AOR = 2.6; 95% CI 1.0, 6.4), and individuals with frequent outdoor activity were 16.4 times more vulnerable than individuals with limited outdoor activities (AOR = 16.4, 95% CI 1.8, 147.9). Furthermore, awareness about malaria transmission was significantly associated with the prevalence of malaria.

Conclusions

Malaria is still a public health problem in Dembiya district irrespective of the past and existing vector control interventions. Therefore, the authorities should work on designing alternative intervention strategies targeting outdoor malaria transmission and improving community awareness about malaria transmission and control methods in the study area. For this, continuous monitoring of vectors’ susceptibility, density, and behaviour is very important in such areas.

Residual malaria in Jazan region, southwestern Saudi Arabia: the situation, challenges and climatic drivers of autochthonous malaria

Background

Saudi Arabia and Yemen are the only two countries in the Arabian Peninsula that are yet to achieve malaria elimination. Over the past two decades, the malaria control programme in Saudi Arabia has successfully reduced the annual number of malaria cases, with the lowest incidence rate across the country reported in 2014. This study aims to investigate the distribution of residual malaria in Jazan region and to identify potential climatic drivers of autochthonous malaria cases in the region.

Methods

A cross-sectional study was carried out from 1 April 2018 to 31 January 2019 in Jazan region, southwestern Saudi Arabia, which targeted febrile individuals attending hospitals and primary healthcare centres. Participants’ demographic data were collected, including age, gender, nationality, and residence. Moreover, association of climatic variables with the monthly autochthonous malaria cases reported during the period of 2010–2017 was retrospectively analysed.

Results

A total of 1124 febrile subjects were found to be positive for malaria during the study period. Among them, 94.3 and 5.7% were infected with Plasmodium falciparum and Plasmodium vivax, respectively. In general, subjects aged 18–30 years and those aged over 50 years had the highest (42.7%) and lowest (5.9%) percentages of malaria cases. Similarly, the percentage of malaria-positive cases was higher among males than females (86.2 vs 13.8%), among non-Saudi compared to Saudi subjects (70.6 vs 29.4%), and among patients residing in rural rather than in urban areas (89.8 vs 10.2%). A total of 407 autochthonous malaria cases were reported in Jazan region between 2010 and 2017. Results of zero-inflated negative binomial regression analysis showed that monthly average temperature and relative humidity were the significant climatic determinants of autochthonous malaria in the region.

Conclusion

Malaria remains a public health problem in most governorates of Jazan region. The identification and monitoring of malaria transmission hotspots and predictors would enable control efforts to be intensified and focused on specific areas and therefore expedite the elimination of residual malaria from the whole region.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-021-03846-4.

A Bayesian Spatio-Temporal Analysis of Malaria in the Greater Accra Region of Ghana from 2015 to 2019

The Greater Accra Region is the smallest of the 16 administrative regions in Ghana. It is highly populated and characterized by tropical climatic conditions. Although efforts towards malaria control in Ghana have had positive impacts, malaria remains in the top five diseases reported at healthcare facilities within the Greater Accra Region. To further accelerate progress, analysis of regionally generated data is needed to inform control and management measures at this level. This study aimed to examine the climatic drivers of malaria transmission in the Greater Accra Region and identify inter-district variation in malaria burden. Monthly malaria cases for the Greater Accra Region were obtained from the Ghanaian District Health Information and Management System. Malaria cases were decomposed using seasonal-trend decomposition, based on locally weighted regression to analyze seasonality. A negative binomial regression model with a conditional autoregressive prior structure was used to quantify associations between climatic variables and malaria risk and spatial dependence. Posterior parameters were estimated using Bayesian Markov chain Monte Carlo simulation with Gibbs sampling. A total of 1,105,370 malaria cases were recorded in the region from 2015 to 2019. The overall malaria incidence for the region was approximately 47 per 1000 population. Malaria transmission was highly seasonal with an irregular inter-annual pattern. Monthly malaria case incidence was found to decrease by 2.3% (95% credible interval: 0.7–4.2%) for each 1 °C increase in monthly minimum temperature. Only five districts located in the south-central part of the region had a malaria incidence rate lower than the regional average at >95% probability level. The distribution of malaria cases was heterogeneous, seasonal, and significantly associated with climatic variables. Targeted malaria control and prevention in high-risk districts at the appropriate time points could result in a significant reduction in malaria transmission in the Greater Accra Region.

Malaria prevention and treatment in migrant agricultural workers in Dangur district, Benishangul-Gumuz, Ethiopia: social and behavioural aspects

BACKGROUND

Sixty percent of the Ethiopia population is at risk of malaria, with the highest prevalence reported in Gambella (6%) and Benishangul-Gumuz (3%) regions. Within these regions are large agricultural developments with high numbers of seasonal migrant workers. The migrant workers are believed to be at increased risk for malaria infection due to their poor living conditions and outdoor activities, but there is little information on their specific behaviours and health risks. This study was conducted to address this gap.

METHODS

Quantitative observations were conducted from September to December 2017 in the Benishangul-Gumuz Region. The nightly routines of mobile migrant workers were observed every month for 4 consecutive months. The study team collected quantitative data including nocturnal behavioural observations of worker living conditions, malaria prevention efforts, and work activities and surveys of worker representatives. Qualitative data was collected from migrant workers, farm managers and local health providers using focus group discussions and semi-structured interviews.

RESULTS

Migrant workers arrived in the study area during the peak malaria transmission season and the workers in focus groups reported repeated cases of malaria during their stay on the farms. Overall, less than a quarter of the migrant workers were sleeping under a mosquito net by midnight in all 4 observation months. Some work activities also took place outdoors at night. The study additionally found a lack of access to malaria prevention and treatment at the farms and challenges in utilizing local public health facilities.

CONCLUSIONS

There is a need to better address malaria prevention and treatment needs among migrant workers in Ethiopia through outreach from existing healthcare infrastructure and within the farms themselves. This will help prevent malaria transmission both within this population and prevent transmission of malaria back to home communities in lower burden areas in Ethiopia.

Prevalence of Malaria among Adults in Ethiopia: A Systematic Review and Meta-Analysis

Background

Malaria is one of the leading causes of mortality and morbidity in tropical and subtropical regions. The bulk of the global malaria burden is in sub-Saharan African countries, including Ethiopia. Malaria adversely affects the health of the peoples as well as the economic development of many developing countries including Ethiopia.

Methods

This review article was reported according to PRISMA guidelines. Related published articles were searched from online public databases, such as PubMed, Google Scholar, and ScienceDirect. The search approach used to retrieve related articles were "prevalence," "malaria," "adults," and "Ethiopia." The quality of articles was assessed using Joana Brigg's Institute (JBI) critical appraisal checklist. The meta-analysis was computed using STATA version 14. The pooled prevalence estimates with 95% confidence interval were analyzed using a random-effect model, and the possible source of heterogeneity across studies was indicated through subgroup analysis, inverse of variance (I ²), and time series analysis. The presence of publication bias was evaluated using funnel plots and Egger's regression test.

Results

Out of 144 studies collected, only eight full-text articles were screened and included in the final quantitative meta-analysis. The pooled prevalence of malaria among adults in Ethiopia was 13.61%. Subgroup analysis based on types of malaria cases showed that the prevalence of malaria among symptomatic and asymptomatic adults was 15.34% and 11.99%, respectively. Similarly, regional subgroup analysis showed that the highest malaria prevalence was recorded in Southern Nations, Nationalities, and Peoples' Region (SNNPR) (16.17%) followed by Oromia Regional State (13.11%) and Amhara Regional State (12.41%). Discussion and Conclusion. The current systematic review and meta-analysis showed that the pooled prevalence of malaria among adults was found to be greater than the general population and nearly equal to pregnant women. Therefore, the current prevention and control measures, which are related to both vectors and parasites, should be strengthened.

Prevalence and association of malaria with ABO blood group and hemoglobin level in individuals visiting Mekaneeyesus Primary Hospital, Estie District, northwest Ethiopia: a cross-sectional study

Malaria is a serious and sometimes fatal mosquito-borne disease caused by protozoan parasite of the genus Plasmodium. ABO blood group antigens represent polymorphic traits inherited among individuals and populations. Differences in blood group antigen expression can increase or decrease host susceptibility to many infections. This study was undertaken to determine the prevalence of malaria and its possible association with ABO blood group and hemoglobin level among individuals attending Mekaneeyesus Primary Hospital, Estie District, northwestern Ethiopia. Sociodemographic variables and relevant data were collected from 390 randomly selected individuals through structured questionnaire. Then, thick and thin smears were prepared from finger pricked blood samples, stained, and examined microscopically for detection and identification of malaria parasites. ABO blood group and hemoglobin levels of the same subjects were also determined. The data generated were analyzed for descriptive and logistic regression models. Variables with p value < 0.05 in multivariable logistic regression were considered explanatory variables. The overall prevalence of malaria was 8.5%; Plasmodium vivax (5.6%) was the most predominant, followed by P. falciparum (2.3%), and mixed infection of the two species (0.5%). In our study, being male (AOR = 3.48), under-five years of age (AOR = 72.84), rural residence (AOR = 2.64), and failing to use bed net (AOR =4.65) were significantly associated with the risk of malaria. Most (14.6%) of malaria-positive cases were among individuals with blood group "A," while the least numbers of cases were among subjects with blood group "O." Individuals with blood group "A" were about four times at risk of malaria as compared to individuals with blood group "O" (AOR= 3.74). The prevalence of anemia was 23.1% and significantly associated with malaria (p<0.05). Prevalence of malaria in this study is still higher compared to some of previous reports from Ethiopia. Thus, there is a need to intensify effort in malaria prevention among potentially at risk segments of population, including males, rural residents, and under-five children, and promotion of ITNs use in the community. Supplementation of iron-rich diet for iron-deficient anemia people is needed. Further in-depth investigation is also necessary to clearly establish the role that ABO blood group plays in malaria.

Past eight-year malaria data in Gedeo zone, southern Ethiopia: trend, reporting-quality, spatiotemporal distribution, and association with socio-demographic and meteorological variables

Background

Informed decision making is underlined by all tiers in the health system. Poor data record system coupled with under- (over)-reporting of malaria cases affects the country’s malaria elimination activities. Thus, malaria data at health facilities and health offices are important particularly to monitor and evaluate the elimination progresses. This study was intended to assess overall reported malaria cases, reporting quality, spatiotemporal trends and factors associated in Gedeo zone, South Ethiopia.

Methods

Past 8 years retrospective data stored in 17 health centers and 5 district health offices in Gedeo Zone, South Ethiopia were extracted. Malaria cases data at each health center with sociodemographic information, between January 2012 and December 2019, were included. Meteorological data were obtained from the national meteorology agency of Ethiopia. The data were analyzed using Stata 13.

Results

A total of 485,414 suspected cases were examined for malaria during the previous 8 years at health centers. Of these suspects, 57,228 (11.79%) were confirmed malaria cases with an overall decline during the 8-year period. We noted that 3758 suspected cases and 467 confirmed malaria cases were not captured at the health offices. Based on the health centers records, the proportions of Plasmodium falciparum (49.74%) and P. vivax (47.59%) infection were nearly equivalent (p = 0.795). The former was higher at low altitudes while the latter was higher at higher altitudes. The over 15 years of age group accounted for 11.47% of confirmed malaria cases (p < 0.001). There was high spatiotemporal variation: the highest case record was during Belg (12.52%) and in Dilla town (18,150, 13.17%, p < 0.001) which is located at low altitude. Monthly rainfall and minimum temperature exhibited strong associations with confirmed malaria cases.

Conclusion

A notable overall decline in malaria cases was observed during the eight-year period. Both P. falciparum and P. vivax were found at equivalent endemicity level; hence control measures should continue targeting both species. The noticed under reporting, the high malaria burden in urban settings, low altitudes and Belg season need spatiotemporal consideration by the elimination program.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-05783-8.

Five-Year Trend Analysis of Malaria Prevalence in Dembecha Health Center, West Gojjam Zone, Northwest Ethiopia: A Retrospective Study

Background

Malaria is a mosquito-borne infectious disease known to cause significant numbers of morbidities and mortalities across the globe. In Ethiopia, its transmission is generally seasonal and highly unstable due to variations in topography and rainfall patterns. Studying the trends in malaria in different setups is crucial for area-specific evidence-based interventions, informed decisions, and to track the effectiveness of malaria control programs. The trend in malaria infections in the area has not been documented. Hence, this study aimed to assess the five-year trend in microscopically confirmed malaria cases in Dembecha Health Center, West Gojjam Zone, Amhara national regional state, Ethiopia.

Methods

A health facility-based retrospective study was conducted in Dembecha Health Center from February to April 2018. All microscopically confirmed malaria cases registered between 2011/12 and 2015/16 were carefully reviewed from laboratory record books and analyzed accordingly.

Results

A total of 12,766 blood films were requested over the last five years at Dembecha Health Center. The number of microscopically confirmed malaria cases was 2086 (16.34%). The result showed a fluctuating yet declining trend in malaria infections. The highest number of cases was registered in 2012/13, while the lowest was in 2015/16. Males and age groups >20 constituted 58.9% and 44.2% of the patients, respectively, being the hardest hit by malaria in the area. Malaria existed in almost every month and seasons. Plasmodium falciparum was the predominant species. The highest peak of malaria infections was observed in the late transition (October-December) 799 (38.3%) and early transition (May-June) 589 (28.2%) seasons.

Conclusion

Although the results indicate a fluctuating yet declining trend, the prevalence of confirmed malaria cases in the area remains alarming and indicates a major public health burden. Therefore, close monitoring and intervention measures to control malaria infections in the area and also to tackle the dominant species, Plasmodium falciparum, are necessitated accordingly.

Determinants of malaria among under-five children in Ethiopia: Bayesian multilevel analysis

BACKGROUND

In Ethiopia, malaria is one of the public health problems, and it is still among the ten top leading causes of morbidity and mortality among under-five children. However, the studies conducted in the country have been inconclusive and inconsistent. Thus, this study aimed to assess factors associated with malaria among under-five children in Ethiopia.

METHODS

We retrieved secondary data from the malaria indicator survey data collected from September 30 to December 10, 2015, in Ethiopia. A total of 8301 under-five-year-old children who had microscopy test results were included in the study. Bayesian multilevel logistic regression models were fitted and Markov chain Monte Carlo simulation was used to estimate the model parameters using Gibbs sampling. Adjusted Odd Ratio with 95% credible interval in the multivariable model was used to select variables that have a significant association with malaria.

RESULTS

In this study, sleeping under the insecticide-treated bed nets during bed time (ITN) [AOR 0.58,95% CI, 0.31-0.97)], having 2 and more ITN for the household [AOR 0.43, (95% CI, 0.17-0.88)], have radio [AOR 0.41, (95% CI, 0.19-0.78)], have television [AOR 0.19, (95% CI, 0.01-0.89)] and altitude [AOR 0.05, (95% CI, 0.01-0.13)] were the predictors of malaria among under-five children.

CONCLUSIONS

The study revealed that sleeping under ITN, having two and more ITN for the household, altitude, availability of radio, and television were the predictors of malaria among under-five children in Ethiopia. Thus, the government should strengthen the availability and utilization of ITN to halt under-five mortality due to malaria.

Spatio-Temporal Dynamic of Malaria Incidence: A Comparison of Two Ecological Zones in Mali

Malaria transmission largely depends on environmental, climatic, and hydrological conditions. In Mali, malaria epidemiological patterns are nested within three ecological zones. This study aimed at assessing the relationship between those conditions and the incidence of malaria in Dangassa and Koila, Mali. Malaria data was collected through passive case detection at community health facilities of each study site from June 2015 to January 2017. Climate and environmental data were obtained over the same time period from the Goddard Earth Sciences (Giovanni) platform and hydrological data from Mali hydraulic services. A generalized additive model was used to determine the lagged time between each principal component analysis derived component and the incidence of malaria cases, and also used to analyze the relationship between malaria and the lagged components in a multivariate approach. Malaria transmission patterns were bimodal at both sites, but peak and lull periods were longer lasting for Koila study site. Temperatures were associated with malaria incidence in both sites. In Dangassa, the wind speed (p = 0.005) and river heights (p = 0.010) contributed to increasing malaria incidence, in contrast to Koila, where it was humidity (p < 0.001) and vegetation (p = 0.004). The relationships between environmental factors and malaria incidence differed between the two settings, implying different malaria dynamics and adjustments in the conception and plan of interventions.

Modeling an association between malaria cases and climate variables for Keonjhar district of Odisha, India: a Bayesian approach

Malaria, a vector-borne disease, is a significant public health problem in Keonjhar district of Odisha (the malaria capital of India). Prediction of malaria, in advance, is an urgent need for reporting rolling cases of disease throughout the year. The climate condition do play an essential role in the transmission of malaria. Hence, the current study aims to develop and assess a simple and straightforward statistical model of an association between malaria cases and climate variates. It may help in accurate predictions of malaria cases given future climate conditions. For this purpose, a Bayesian Gaussian time series regression model is adopted to fit a relationship of the square root of malaria cases with climate variables with practical lag effects. The model fitting is assessed using a Bayesian version of R² (RsqB). Whereas, the predictive ability of the model is measured using a cross-validation technique. As a result, it is found that the square root of malaria cases with lag 1, maximum temperature, and relative humidity with lag 3 and 0 (respectively), are significantly positively associated with the square root of the cases. However, the minimum and average temperatures with lag 2, respectively, are observed as negatively (significantly) related. The considered model accounts for moderate amount of variation in the square root of malaria cases as received through the results for RsqB. We also present Absolute Percentage Errors (APE) for each of the 12 months (January-December) for a better understanding of the seasonal pattern of the predicted (square root of) malaria cases. Most of the APEs obtained corresponding to test data points is reasonably low. Further, the analysis shows that the considered model closely predicted the actual (square root of) malaria cases, except for some peak cases during the particular months. The output of the current research might help the district to develop and strengthen early warning prediction of malaria cases for proper mitigation, eradication, and prevention in similar settings.

Trend of malaria prevalence in Wolkite health center: an implication towards the elimination of malaria in Ethiopia by 2030

Background

Malaria is one of the main public health challenges in Ethiopia that hinder the productivity and development of the country. In 2018, Ethiopia is on track to minimize the incidence of malaria by 40% as per its 2020 malaria reduction strategy. Currently, Ethiopia is working to eliminate malaria in 2030 by extending the 2020 strategy. Hence, this study aimed to analyze the trend of malaria prevalence in Wolkite health center, Gurage zone, Southern Central Ethiopia from 2015 to 2018.

Methods

A retrospective study was conducted to determine the prevalence of malaria by reviewing the malaria registration laboratory logbook at Wolkite health center from 2015 to 2018. For all patients, blood films were done for the detection of malaria cases. All the socio-demographic data, year, month and malaria data were collected using a predesigned data collection sheet from January to March, 2019.

Results

From a 121,230 clinically malaria suspected patients, the overall prevalence of microscopically confirmed cases were 8.56% (n = 10,379/121,230). Plasmodium vivax was the most predominant species accounted for 69.7% (n = 7237/10,379) followed by Plasmodium falciparum 29.3% (n = 3044/10,379). Age group > 15 years old were more affected by malaria accounting 54% (n = 5609/10,379) and malaria cases regarding sex were proportional (51.1% of males and 48.3% of female). Among the catchment areas, a higher number of malaria prevalence was recorded in the Wolkite town 66.2% (n = 0.6538/10,379). Higher malaria cases were shown in the season of Spring 29.8% (n = 3096/10,379) while lower cases 20.4% (n = 2123/10,379) were seen in the Winter season.

Conclusion

The prevalence of malaria in Wolkite health center showed a consistent downward trend from the year of 2015–2018. Importantly, the higher prevalence of P. vivax seems overlooked in the study area. Therefore, malaria prevention and control strategy should be reinforced to reduce the prevalence of malaria in the study area.

Seasonal pattern of malaria cases and the relationship with hydrologic variability in the Amazonas State, Brazil

INTRODUCTION

Malaria is an infectious disease of high transmission in the Amazon region, but its dynamics and spatial distribution may vary depending on the interaction of environmental, socio-cultural, economic, political and health services factors.

OBJECTIVE

To verify the existence of malaria case patterns in consonance with the fluviometric regimes in Amazon basin.

METHOD

Methods of descriptive and inferential statistics were used in malaria and water level data for 35 municipalities in the Amazonas State, in the period from 2003 to 2014.

RESULTS

The existence of a tendency to modulate the seasonality of malaria cases due to distinct periods of rivers flooding has been demonstrated. Differences were observed in the annual hydrological variability accompanied by different patterns of malaria cases, showing a trend of remodeling of the epidemiological profile as a function of the flood pulse.

CONCLUSION

The study suggests the implementation of regional and local strategies considering the hydrological regimes of the Amazon basin, enabling municipal actions to attenuate the malaria in the Amazonas State.

A survey of management practices and major diseases of dairy cattle in smallholdings in selected towns of Jimma zone, south-western Ethiopia

Context Smallholder dairy farming is becoming an important source of food, income and employment for many urban dwellers in Ethiopia. However, suboptimal productivity is a major constraint due to diseases and poor management practices. Aims The present work aimed at assessing management practices, dairy cattle diseases, and methods used by farmers to identify diseases on smallholdings in selected towns of Jimma zone, south-western Ethiopia. Methods Data for the study were obtained by surveying 52 dairy-keeping farmers by using a semi-structured questionnaire and personal observations. Key results The mean herd size of indigenous and crossbred cattle was 5 ± 0.04 and 2 ± 0.4 respectively. Natural pasture was the main source of feed with supplementation, mainly with agro-industrial by-products, concentrate mixes, non-conventional feeds and crop residues. In total, 75% of the respondents practiced a free-grazing system. Most (64%) of the respondents used natural service for breeding. In all, 64% and 35% of the respondents washed their hands and the teats respectively, before milking. In the order of decreasing percentage of respondents, the most frequently reported dairy cattle health problems were tick infestation, mastitis, lumpy skin disease, blackleg, heart water, facioliasis, trypanosomiasis, foot-and-mouth disease, pasteurellosis, brucellosis and anthrax. Repeated breeding, retained fetal membranes, abortion, stillbirths and dystocia were the common reproductive health problems, in a decreasing order of the reported percentage. Lumpy skin disease was reported as a major cause of calf and lactating-cow deaths. A total of 89% of the respondents used veterinary medicines to treat their sick animals. About 24% of the respondents stated culling of their animals due to old age, lack of space, infertility, feed shortage, need for cash and low production, in a decreasing order of importance. Conclusions The results showed farmers are well knowledgeable in cattle production practices and are actually mitigating effects of most disease challenges in their farms, which may have resulted in low milk productivity. Implications The farmers in the current study had some knowledge of milk production activities that may be recommended for similar settings, especially on how to manage dairy cattle production under smallholder farms, obviously including the occurrence of diseases, which they are managing appropriately with available technologies including vaccines and treatment. These could be used as baseline data by dairy stakeholders and policy makers during the formulation and implementation of policies for sustainable growth and development of smallholder dairy for similar settings.

Community based integrated vector management for malaria control: lessons from three years' experience (2016-2018) in Botor-Tolay district, southwestern Ethiopia

BACKGROUND

Integrated vector management (IVM) remains a key strategy in the fight against vector-borne diseases including malaria. However, impacts of the strategy should be regularly monitored based on feedback obtained through research. The objective of this study was to assess the impact of IVM for malaria control in Botor-Tolay district, southwestern Ethiopia after three years (2016-2018) of IVM implementation.

METHOD

Prior to the implementation of IVM, a survey of socio-demographic, malaria burden, and communities' perception towards malaria control was conducted in 200 households selected at random from 12 villages using standard questionnaire. Households were revisited after three years of project implementation for impact assessment. Compiled malaria case data was obtained from district health bureau for the three years period of the study while adult mosquito collection was conducted during each year using CDC light traps. Monthly larval mosquito collections were made each year using standard dipping method. Community education and mobilization (CEM) was made through different community-based structures.

RESULTS

The proportion of respondents who sought treatment in health facilities showed a significant increase from 76% in 2015 to 90% in 2018(P < 0.001). An average of 6.3 working and 2.3 school days were lost per year in a household due to parents and children falling sick with malaria. Malaria costs in a household in Botor-Tolay averaged 13.3 and 4.5 USD per episode for medical treatment and transportation respectively. Significantly fewer adult mosquitoes were collected in 2018 (0.37/house/trap-night) as compared to 2015 (0.73/house/trap-night) (P < .001). Malaria cases significantly declined in 2018 (262) when compared to the record in 2015 (1162) (P < 0.001). Despite improved human behavioral changes towards mosquito and malaria control, there were many setbacks too. These include reluctance to seek treatment in a timely manner, low user compliance of LLINs and low net repairing habit.

CONCLUSION

The coordinated implementation of community-based education, environmental management, larviciding together with main core vector control interventions in Botor-Tolay district in Southwestern Ethiopia have contributed to significant decline in malaria cases reported from health facilities. However, commitment to seeking treatment by people with clinical symptoms of malaria and to repair of damaged mosquito nets remained low.

Epidemiology and distribution of Plasmodium vivax malaria in Sudan

BACKGROUND

Plasmodium vivax malaria has been recognised as an important cause of morbidity in several African countries. The prevalence was previously estimated as 2-5% in eastern Sudan. These estimates are observed to be rising and spreading continuously. The present study was undertaken to investigate the situation of distribution and epidemiology of P. vivax malaria in Sudan.

METHODS

Cross-sectional malaria surveys carried out in hospitals and health centres covered 21 sites in 10 states. Data and blood samples were collected from 1226 clinically investigated suspected malaria cases of both genders and all ages. Microscopically detected malaria parasites were confirmed by PCR.

RESULTS

The overall prevalence of P. vivax among the malaria cases was 26.6%. The prevalence showed significant variations between the states (p<0.001), which could be explained by differences in population movement, the presence of refugees and proximity to endemic neighbouring countries. It also varied significantly with residence status (p<0.001), reflecting the stability of transmission.

CONCLUSION

Although malaria in Sudan is still largely attributed to Plasmodium falciparum, P. vivax has been rising with worrying proportions and spreading to new areas. The emergence and marked increase of P. vivax poses new challenges to malaria treatment and control in Sudan.