Distribution Of Malaria Cases Research Articles

Analysis of Distribution Patterns of Environmental Risk Factors with Malaria Incidents in the Working Area of the Tanjung Tiram Community Health Center, Batu Bara Regency

<p><em>Environmental conditions have a big influence on the incidence of malaria because a bad environment can increase the breeding and proliferation of Anopheles mosquitoes. The aim of this research is to determine environmental risk factors and distribution patterns of malaria in the Tanjung Tiram Community Health Center working area, Batubara Regency. This research method is analytical observational with a case control research design and an ecological approach. This research was conducted in the working area of the Tanjung Tiram Health Center, Batu Bara Regency, which was carried out from April to July 2023. Population 40,604 people. The sampling technique was purposive sampling so that the research sample was 100 people. Data collection uses questionnaires and observation sheets. Data analysis using the bivariate Chi square test on SPSS version 20 software and Analysis of malaria case distribution mapping using the Geographic Information System (GIS) application to describe the distribution pattern of malaria in Batubara Regency. The results of the study show that there is a relationship between environmental risk factors such as ceilings (p-value=0.000), wall type (p-value=0.000), ventilation (p-value=0.000), wall density (p-value=0.000), partitions on windows (p-value=0.000), the presence of puddles (p-value=0.000), gutters (p-value=0.000) and swamps around the house (p-value=0.000). The distribution of Malaria cases in Tanjung Tiram District, Batubara Regency is not spread across all areas in the district, this means that the highest number of malaria cases occur in mixed plantation areas. By depicting the distribution pattern in the form of a map, it can optimize the reduction in the incidence of malaria cases.</em></p><p><em> </em></p><strong><em>Keywords: Environment, Geographic Information System, Malaria</em></strong>

Use of Mapping Technologies to Study the Spatial Distribution of Malaria Incidence in Vietnam

Background: Malaria is one of the major public health issues globally. Malaria infection spreads through mosquito bites from infected female Anopheles mosquitoes. This study aims to apply mapping technologies to investigate the spatial distribution of malaria cases and incidence in Vietnam. Materials and Methods: Malaria cases in 2019 were first collected from the websites of the Vietnam Ministry of Health (VMH). The incidence of malaria will be then computed. The histogram is employed to study the distribution of malaria cases and incidence. Mapping technologies is then used to study the spatial distribution of malaria cases and incidence. In addition, a scatter plot is also used to investigate the relationship between population density and the incidence of malaria. Finally, results and findings will be discussed and summarised. Results: the study results showed that the highest rate of malaria infection was detected in Gia Lai, followed by Phu Yen, Dak Lak, and Binh Phuoc. Areas of high malaria infection rates were mainly concentrated in rural areas in the south-central region having with high vegetation coverage. Whereas, areas with no or low malaria infection rates were mainly concentrated in urban areas in the northeastern and southeastern regions of Vietnam. In addition, there was a negative correlation between population density and the incidence of malaria. Conclusion: It can be concluded that the combination of histograms, mapping technologies and a scatter plot prove their effectiveness in the study of malaria. Findings in this study provide an insight into how to apply mapping technologies to study and prevent the spread of such an infectious disease as malaria. Keywords: Spatial distribution, Malaria cases, Malaria incidence, Histogram, Scatter plot, Mapping technologies.

Environmental Vulnerability against the Presence of Anopheles spp. with Malaria Cases in North Jakarta

There are several locations in DKI Jakarta which have the potential become breeding places for Anopheles spp larvae. The aim of this study was to analyze environmental vulnerability to the presence of Anopheles spp. larvae with malaria cases using a geographic information system approach. This study was an observational study with a cross sectional design. This study was carried out in March – June 2023 in North Jakarta City, DKI Jakarta. The sample consists of data from all malaria patients from 2020-2023 in North Jakarta. The global positioning system coordinates were taken at the addresses of malaria patients. In addition, data on the presence of Anopheles spp. obtained from larval surveys conducted in Cilincing and Penjaringan Sub-Districts and the coordinates for the habitat of Anopheles spp. larvae. The GPS points obtained were then used for spatial analysis. The distribution of malaria cases was random, while the distribution of Anopheles larvae was dispersed. Buffering zone >1000 m from the breeding site indicated that it does not have the potential in malaria transmission due to malaria patients were at a long distance from the breeding site of Anopheles spp. and flight distance of Anopheles spp. not exceeding 1000 m

Estimated distribution of malaria cases among children in sub-Saharan Africa by specified age categories using data from the Global Burden of Diseases 2019

BackgroundChildren in sub-Saharan Africa (SSA) remain the most vulnerable to malaria and malaria mortality. This study estimated the disease burden and distribution of Plasmodium falciparum malaria among children with age categories (0 to < 2 years, 2 to < 6 years, 6 to < 12 years, ≥ 12 years) in SSA.MethodsData on the number of cases and incidence rates of P. falciparum malaria by age group from the Institute of Health Metrics and Evaluation (GBD 2019) for 11 countries in SSA was employed in this study. The best-fitting distribution of P. falciparum malaria cases by prespecified age categories was derived using a combination of a Log-normal and Weibull distribution.ResultsPlasmodium falciparum malaria was 15.4% for ages 0 to < 2 years, 30.5% for 2 to < 6 years, 17.6% for 6 to < 12 years, and 36.5% for ≥ 12 years based on data from countries in SSA. The results have important implications for the current drive by the FDA and EMA to ensure the representativeness of real-world populations in clinical trials evaluating the safety and efficacy of medication exposure.ConclusionsThe theoretical distributions of P. falciparum malaria will help guide researchers in ensuring that children are appropriately represented in clinical trials and other interventions aiming to address the current burden of malaria in SSA.

Analysis of Malaria Transmission Dynamics at Borobudur Health Center, Magelang Regency (Case Study 2021-2022)

Introduction: Magelang District received a malaria elimination certificate in 2014. No cases found at Borobudur Health Center since 2009 but in October 2021, there was a spike in the number of patients, with 38 instances spread across Giripurno Village, Giritengah Village, and Majaksingi Village. Therefore, it is necessary to study the dynamics of malaria transmission so that the methods of malaria transmission are known to prevent extraordinary malaria cases. Methods: This is qualitative research with a phenomenological approach. This study was conducted in 2023 by reviewing cases from 2021–2022. The respondents in this study included 38 people with malaria. This research uses descriptive analysis assisted by GIS applications to determine the distribution of malaria cases. Results and Discussion: Data processing results for 38 respondents in three villages revealed 23 index cases. Of the 23 cases, nine were within a radius of no more than 400 m and occurred within three days, thus including cluster classification. Theoretically, the same vector transmits it and has a high vectorial capacity. The other 15 patients were suspected to have secondary cases, with two transferred from the first case. The results of the breeding place survey or the potential breeding place after rearing revealed the species Anopheles balabacensis. Other predictors of malaria transmission are optimal temperature and humidity, environment, livestock places to rest mosquitoes, and patient behavior that causes a high frequency of mosquitoes biting humans. Conclusion: In this case, the transmission model was a cluster, and 100% of the cases were indigenous.

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

BackgroundMillions 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.MethodsMalaria 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.ResultsAverage 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.ConclusionThe 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).

Civil Engineering and Malaria Risk: A Descriptive Study in a Rural Area of Cubal, Angola

(1) Background: Angola is among the high-burden countries with malaria cases globally. After 2013, we suspected an increase in the number of malaria cases in Cubal (Angola), previously in decline. Our objective was to evaluate the incidence rate in Cubal, overall and by neighborhood, for 2014, 2015, and 2016. (2) Methods: A retrospective, observational study was performed in Cubal (Angola) from January 2014 to December 2016, including all patients with a microbiologically confirmed diagnosis, treated at Cubal's Hospitals for this period of time. The principal variables calculated were the incidence rates of 2014, 2015, and 2016 in Cubal (overall and by neighborhood). (3) Results: There were 3249 malaria cases. The incidence rates were 2.27, 10.73, and 12.40 cases per 1000 inhabitants in 2014, 2015, and 2016, respectively. In the neighborhood, Hamavoko-Kasseke, there was a 10.73-fold increase in incidence during this period. Additionally, Hamavoko-Kasseke presents an anomalous distribution of malaria cases. (4) Conclusions: We observed an increase in the incidence of malaria in Cubal during the three-year study period. The case distribution was highly heterogeneous with hyperendemic areas, and we found a chronobiological association between the construction of a civil engineering project. This information could be useful for deciding which malaria control strategies must be implemented in this area.

Spatial pattern and predictors of malaria in Ethiopia: Application of auto logistics regression.

IntroductionMalaria is a severe health threat in the World, mainly in Africa. It is the major cause of health problems in which the risk of morbidity and mortality associated with malaria cases are characterized by spatial variations across the county. This study aimed to investigate the spatial patterns and predictors of malaria distribution in Ethiopia.MethodsA weighted sample of 15,239 individuals with rapid diagnosis test obtained from the Central Statistical Agency and Ethiopia malaria indicator survey of 2015. Global Moran’s I and Moran scatter plots were used in determining the distribution of malaria cases, whereas the local Moran’s I statistic was used in identifying exposed areas. The auto logistics spatial binary regression model was used to investigate the predictors of malaria.ResultsThe final auto logistics regression model was reported that male clients had a positive significant effect on malaria cases as compared to female clients [AOR = 2.401, 95% CI: (2.125–2.713) ]. The distribution of malaria across the regions was different. The highest incidence of malaria was found in Gambela [AOR = 52.55, 95%CI: (40.54–68.12)] followed by Beneshangul [AOR = 34.95, 95%CI: (27.159–44.963)]. Similarly, individuals in Amhara [AOR = 0.243, 95% CI:(0.195–0.303], Oromiya [AOR = 0.197, 955 CI: (0.158–0.244)], Dire Dawa [AOR = 0.064, 95%CI(0.049–0.082)], Addis Ababa[AOR = 0.057,95%CI:(0.044–0.075)], Somali[AOR = 0.077,95%CI:(0.059–0.097)], SNNPR[OR = 0.329, 95%CI: (0.261–0.413)] and Harari [AOR = 0.256, 95%CI:(0.201–0.325)] were less likely to had low incidence of malaria as compared with Tigray. Furthermore, for one meter increase in altitude, the odds of positive rapid diagnostic test (RDT) decreases by 1.6% [AOR = 0.984, 95% CI: (0.984–0.984)]. The use of a shared toilet facility was found as a protective factor for malaria in Ethiopia [AOR = 1.671, 95% CI: (1.504–1.854)]. The spatial autocorrelation variable changes the constant from AOR = 0.471 for logistic regression to AOR = 0.164 for auto logistics regression.ConclusionsThis study found that the incidence of malaria in Ethiopia had a spatial pattern which is associated with socio-economic, demographic, and geographic risk factors. Spatial clustering of malaria cases had occurred in all regions, and the risk of clustering was different across the regions. The risk of malaria was found to be higher for those who live in soil floor-type houses as compared to those who lived in cement or ceramics floor type. Similarly, households with thatched, metal and thin, and other roof-type houses have a higher risk of malaria than ceramics tiles roof houses. Moreover, using a protected anti-mosquito net was reducing the risk of malaria incidence.

Malaria Surveillance Mapping in Yogyakarta Special Region, Indonesia

Background: Kulon Progo is one of contributing malaria cases in Indonesia and eliminating incidence malaria still unsolved problem in Indonesia. This study aims to analyze the relationship between mosquito breeding sites, the distribution of malaria cases through Arc-GIS specifically for buffering and spatial analysis in Kulon Progo Regency from 2015 to 2021. Subjects dan Method: This descriptive research retrospective approach was conducted from secondary data on malaria cases in Kulon Progo between 2015 and 2021. The variable research in this study are positive malaria cases diagnosed using the traditional method of thick blood and thin smear. The sampling technique in this study used total sampling, in totally 265 cases were included. The Data on malaria cases in Kulon Progo Health Office were used as instruments to develop the spatial map and questionnaires served as a confirmation sheet for demographic characteristic. GPS (Global Positioning System) 10.3 used to determine the coordinates of malaria cases. Data on malaria cases are presented in a six-year time series. Area classification using Arc-GIS 10.1 software with buffer analysis and visualization data was utilized to determine the distribution pattern of malaria. Results: Incidence declined sharply 23.9 to 0.4 cases per 100,000 in 2015 to 2021. The purely cluster of malaria cases trend were in the watershed area at a distance of &lt;250 meters in Kokap Sub-district. Malaria cases were mostly found in rice fields with a distance of &lt;250 meters in Samigaluh Sub-district. All malaria cases were in the garden areas of &lt;250meters in Nanggulang and the forest area of &gt;250 meters in the Kalibawang Sub-district. Conclusion: Probability of malaria transmission are rivers, rice fields and gardens. It is necessary to hold training on the use of the Arc-GIS application for surveillance officers. Keywords: Gis, malaria, mapping, surveillance. Correspondence: Fatma Nuraisyah, Faculty of Public Health, Universitas Ahmad Dahlan, Indonesia. Kapas street No. 9, Semaki, Special Region of Yogyakarta, Post Box: 55166; email: fatma.nuraisyah@ikm.uad.ac.id. Mobile: 6285747232100. Journal of Epidemiology and Public Health (2022), 07(04): 562-572 https://doi.org/10.26911/jepublichealth.2022.07.04.12 .

SITUASI MALARIA DI KOTA LUBUKLINGGAU PROVINSI SUMATERA SELATAN DALAM MENCAPAI ELIMINASI MALARIA TAHUN 2021

Malaria is a vector borne disease and is one of the leading causes of mortality and morbidity worldwide. In general, the prevalence of malaria parasites differed between age and sex with the highest prevalence occurring in children and women. This study uses secondary data from the Lubuklinggau City Health Office in 2015 - 2018. The number of malaria cases in Lubuklinggau City has decreased during 2015 - 2018. Most cases of malaria occur in women. The distribution of malaria cases was highest in the age group 15 - 64 years and there were still cases in children aged 0 - 5 years. The most common type of Plasmodium found is Plasmodium vivax. To maintain malaria elimination, Lubuklinggau City must eliminate indigenous cases and improve treatment management and management of malaria cases.

Investigation of the Annual and Periodic Distribution of Malaria Cases in Mogadishu, Somalia: A Retrospective Analysis of Four-Year Data

Investigation of the Annual and Periodic Distribution of Malaria Cases in Mogadishu, Somalia: A Retrospective Analysis of Four-Year Data

Socio-Epidemiological Features and Spatial Distribution of Malaria in an Area under Mining Activity in the Brazilian Amazon Region.

Malaria is an acute febrile infectious disease that represents an important public health problem in the Brazilian amazon region. The present study described the socio-epidemiological and spatial characteristics of malaria in a population from the Tapajós mining areas, Pará, Brazilian Amazon. A cross-sectional study, including individuals from Itaituba city, an area under mining activity influence, was conducted. The geographic coordinates were obtained in the field using the Global Positioning System (GPS) Garmin 78csx; for spatial analysis, we used the Kernel Density Estimator with the application of scanning statistics with the SaTScan software. Of the 908 individuals, 311 were positive for malaria. Most of the malaria cases were associated with male individuals, gold miners and with a monthly income of 4-6 salaries. Binary logistic regression analysis demonstrated that gold miners were nearly five times more likely to acquire malaria. In addition, a context of risk for sexually transmitted infections, substance abuse and poor support conditions was observed, worsening the healthcare scenario in this endemic area for malaria. The spatial distribution of malaria cases is irregular in the municipality with hotspot areas located in the Amana Flona that coincide with areas of illegal mining and high human mobility. Finally, the presented socio-epidemiological and spatial distribution data may aid in the development of more effective control measures for malaria in the area.

Epidemic situation and diagnosis of imported malaria before and after malaria elimination in Nanjing City, Jiangsu Province

To analyze the epidemiological characteristics and diagnosis of imported malaria before and after malaria elimination in Nanjing City of Jiangsu Province, so as to provide the scientific evidence for formulating the malaria control strategy after malaria elimination. Data pertaining to the epidemic situation and individual investigation of malaria in Nanjing City before (from 2012 to 2016) and after malaria elimination (from 2017 to 2020) were captured from the National Notifiable Communicable Disease Reporting System and the Information System for Parasitic Diseases Control and Prevention and were analyzed statistically. A total of 178 malaria cases were reported in Nanjing City from 2012 to 2020, and all were imported cases. There were 99 malaria cases reported before malaria elimination in Nanjing City, including 78 cases with Plasmodium falciparum malaria (78.79%), 5 cases with P. vivax malaria (5.05%), 10 cases with P. ovale malaria (10.10%), 3 cases with P. malariae malaria (3.03%) and 3 cases with mixed infections (3.03%), and 79 malaria cases reported after elimination, including 63 cases with P. falciparum malaria (79.75%), 5 cases with P. vivax malaria (6.33%), 9 cases with P. ovale malaria (11.39%), 2 cases with P. malariae malaria (2.53%). There was no significant difference in the proportion of each type of malaria cases in Nanjing City before and after malaria elimination (χ2 =2.400, P > 0.05). Malaria cases mainly acquired Plasmodium infections in African regions, and no significant difference was seen in the proportion of malaria cases returning to Nanjing City from African countries before and after malaria elimination (χ2 = 0.093, P > 0.05). The number of malaria cases peaked in Nanjing City in January and during the period from May to July before elimination, and there was no apparent seasonal variation in the distribution of malaria cases after elimination. The proportion of malaria cases living in Nanjing City was significantly greater after malaria elimination than before elimination (72.15% vs. 55.56%; χ2 = 5.187, P = 0.023). The proportions of businessmen and international students were both 5.05% before malaria elimination, and increased to 15.19% and 13.92% after elimination, respectively (χ2 = 5.229 and 4.229, both P values < 0.05). The percentage of definitive diagnosis of malaria at initial diagnosis was 18.75% in county-level hospitals before malaria elimination and increased to 61.11% after elimination (χ2 = 6.275, P = 0.012), while the proportion of malaria cases with definitive diagnoses in county-level hospitals was 4.04% before malaria elimination and increased to 13.92% after elimination (χ2 = 5.562, P = 0.018). During the period from 2012 to 2020, the proportion of malaria cases with definitive diagnoses within 1 to 3 days post-admission increased from 27.27% in Nanjing City before malaria elimination to 45.57% after elimination (χ2 = 6.433, P = 0.011). The epidemic situation of imported malaria remains serious in Nanjing City during the post-elimination stage, and malaria parasite infections predominantly occur in African regions. In addition, there are changes in regional and occupational distributions of malaria cases and the diagnostic capability of malaria increases in county-level hospitals in Nanjing City after malaria elimination. Further improvements in the malaria surveillance system and the diagnostic and treatment capability of malaria in medical institutions at each level are required to consolidate malaria elimination achievements in Nanjing City.

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.

The top 1%: quantifying the unequal distribution of malaria in Brazil

BackgroundAs malaria endemic countries strive towards elimination, intensified spatial heterogeneities of local transmission could undermine the effectiveness of traditional intervention policy.MethodsThe dynamic nature of large-scale and long-term malaria heterogeneity across Brazilian Amazon basin were explored by (1) exploratory analysis of Brazil’s rich clinical malaria reporting database from 2004 to 2018, and (2) adapting Gini coefficient to study the distribution of malaria cases in the region.ResultsAs transmission declined, heterogeneity increased with cases clustering into smaller subpopulations across the territory. In 2004, the 1% of health units with the greatest number of cases accounted for 46% of all reported Plasmodium vivax cases, whereas in 2018 52% of P. vivax cases occurred in the top 1% of health units. Plasmodium falciparum had lower levels of transmission than P. vivax, and also had greater levels of heterogeneity with 75% of cases occurring in the top 1% of health units. Age and gender stratification of cases revealed peri-domestic and occupational exposure settings that remained relatively stable.ConclusionThe pathway to decreasing incidence is characterized by higher proportions of cases in males, in adults, due to importation, and caused by P. vivax. Characterization of spatio-temporal heterogeneity and risk groups can aid stratification for improved malaria control towards elimination with increased heterogeneity potentially allowing for more efficient and cost-effective targeting. Although distinct epidemiological phenomena were clearly observed as malaria transmission declines, the authors argue that there is no canonical path to malaria elimination and a more targeted and dynamic surveillance will be needed if Brazil decides to adopt the elimination target.

Analisis Spasial Kasus Malaria di Kabupaten Banyumas Tahun 2009-2018

Malaria is still a public health problem in the Banyumas district. Spatial information can be used as a strategy to control malaria. This study aimed to describe malaria cases using spatial analysis in the Banyumas District from 2009 to 2018 based on environmental conditions. This research was quantitative method conducted by a descriptive spatial approach. Data collected by secondary data which was obtained from various sources such as Health Agency, Statistics Indonesia, Indonesian Ministry of National Development, National Institute of Research and Development, and Office of Public Works of Banyumas. The data analysis implemented was descriptive and processed with ArcGis software. The findings illustrated that the number of malaria cases during the 2009-2018 period in Banyumas district was 1624 cases. The most dominant malaria cases distribution were in Sumpiuh and Tambak Subdistrict. The Trend of API from 2009 to 2018 was getting better, 2009 to 2012 found that there were subdistricts with Moderate Case Incidence (MCI) and High Case Incidence (HCI), however, Low Case Incidence (LCI) was present in 2013 to 2018 in Sumpiuh and Kebasen subdistricts and the rests were free from malaria. The results of spatial analysis discovered that most of the malaria cases were in the medium population density area. The distribution of malaria cases has decreased significantly, even though the environmental conditions still potentially transmit malaria.

Epidemiological characteristics of malaria in Henan Province from 1950 to 2019

To analyze the epidemiological characteristics of malaria in Henan Province from 1950 to 2019, so as to provide the scientific evidence for consolidating malaria elimination achievements in the province. The epidemiological situation of malaria and demographic data in Henan Province from 1950 to 2019 were collected, and the statistical analyses were performed using a descriptive epidemiological method. The spatial temporal distribution of malaria cases was identified using the software ArcGIS version 10.3. During the period from 1950 through 2019, the progress of malaria elimination was divided into 4 stages in Henan Province, including the baseline-survey and key-control stage, morbidity-control and incidence-reduction stage, basic-eradication and achievement-consolidation stage and elimination stage. The spatial distribution of malaria cases shifted from south of the Huai River and the plain regions between the Yellow River and Taihang Mountain to the Huang-Huai-Hai Plain and Nanyang Basin, then was concentrated in eastern part of southern Huai River where Anopheles anthropophagus was distributed, and finally was gradually under control following malaria outbreak in Eastern Henan Plain. In addition, the species of Plasmodium changed from P. vivax, P. falciparum and P. malariae co-endemics to a single P. vivax infection, and the current co-endemics of 5 invasive malaria parasites, and the malaria vectors shifted from co-existence of Anopheles sinensis and An. anthropophagus to An. sinensis alone. There has been a large change in the epidemiological characteristics of malaria in Henan Province from 1950 to 2019. Although malaria has been eliminated in Henan Province, the consolidation of the malaria elimination achievements remain a great challenge due to overseas imported malaria.

Influence of Climate on the Spatiotemporal Distribution of Malaria in Thulamela Municipality, Limpopo Province, South Africa

Background: Malaria, though curable, continues to be a major health and socioeconomic challenge. Malaria cases have been on the rise for the last two years in the malaria-endemic region of South Africa. Thulamela Municipality in Limpopo, South Africa, which falls within several municipalities at Vhembe district that are affected by malaria. About 33,448 malaria cases were reported over a period of 20 years (1998 January-2018 December). Objective: The study aims to determine the influence of climate on the spatiotemporal distribution of malaria cases in Thulamela Municipality for the last two decades (1998 January-2018 December). Methods: The analysis is divided into two sections, including temporal and spatial distribution of malaria cases, and the correlating climatic and environmental factors. Time series analysis is conducted to determine the variations of malaria and climate. Malaria and climatic factors (rainfall, maximum temperature, minimum temperature) were globally correlated using matrix scatterplot spearman correlation with a certain significance level. The Ordinary Least Squares (OLS) regression was performed to determine the significant climate factors that locally affect the spatial distribution of malaria cases. The local environmental factor (rivers) was analyzed using buffering and terrain analysis. Results: A positive spearman correlation of the time series was found with the significance level of 0.01. The climate variables were not strongly significant to the spatial distribution of malaria at the village level. The villages which continued to record high malaria cases were in proximity to rivers by 2km. The Thulamela municipality falls within 20-30°C, which is essential for the incubation of mosquitoes and transmission of malaria. The areas receiving about 125 to 135 mm of total monthly rainfall record high malaria cases. The temperature, rainfall, and rivers are important factors for malaria transmission. Conclusion: Knowledge of the drivers of the spatiotemporal distribution of malaria is essential for a predicting system to enhance effective malaria control in communities such as the Thulamela municipality.

The association between malaria incidences and air temperature at Kulon Progo District, Yogyakarta Special Province

Malaria is still a public health problem in Indonesia including in Kulon Progo District, Yogyakarta Special Province. Kulon Progo District remains become malaria endemic area, with significant number of malaria cases for more than the last ten years. Previous studies proved that malaria transmission is associated with climatic conditions. However, these conditions have never been investigated in Kulon Progo District. The aim of this ecological study was to investigate the association between the distribution of malaria cases and climatic condition in the Kulon Progo District using spatial-temporal approach. A total of 1439 malaria cases were collected during the period of 2005-2015. Time-trend, bivariate analysis, and spatial analysis were performed. The results showed that air temperature lag 0 (p = 0.0000; r = 0.5225), air temperature lag 1 (p = 0.0009; r = 0.2850), air temperature lag 2 (p = 0.0329; r = 0.1858) related to the incidence of malaria. Spatial analysis and time-trend analysis also showed direct relationship pattern between malaria and air temperature. In conclusion, there is a relationship between malaria cases and air temperature in Kulon Progo District. Spatial analysis approach is important for early alert system, to decrease morbidity and mortality due to malaria.

Case study of malaria patients: distribution of cases and maps of Anopheles sp. breeding place in Kaligesing sub-district, Purworejo district

Malaria has been a health problem in Indonesia, including in sub-district Kaligesing, district Purworejo of Central Java Province. Malaria has also been identified as an endemic especially in the villages of Jatirejo, Kaliharjo, and Somongari. The purpose of this study was to describe the epidemiology of malaria incidence based on distribution of cases, surrounding house related cases, and the Anopheles breeding place of malaria vectors. This descriptive based research with a case study approach investigated 61 malaria cases as respondents from 2016-2018 in Jatirejo, Kaliharjo and Somongari Villages sampled using total population method. The chosen variables were behaviour and environment of the respondents in relation to the presence of Anopheles vector breeding grounds. Data were analyzed descriptively and displayed in tables and maps. The results of the analysis showed that the average age of the malaria sufferer was 34 years old, male (60.7%), and most of them (45%) were coconut farmers. The most common symptoms of malaria experienced by respondents were fever, chills, headaches, and night sweats. In addition, 24.6% did not use insecticide-treated netting while sleeping. Spatially, the highest distribution of malaria cases was identified in Jatirejo Village, as its topography is plateau with a plantation area. Meanwhile, the existence of breeding places was found surrounding respondents’ houses. To prevent from having malaria, people have been advised to take precautions by wearing long clothes when going out at night, using repellents/anti-mosquito treatments, providing larvicides at breeding sites around their house.