Determinant Factors Influencing Malaria Incidence in an Endemic Area of Sumbawa, Indonesia

The problem faced by manager of malaria programe, especially field workers are low community participation in the implementation of malaria prevention activities, whereas most of the program was in need of community participation to be implemented properly.Design was analytical research with cross sectional approach. The population in this study was all people in Umalor village, District of West Malacca NTT amount 384 families, with Simple Random Sampling technique obtained samples 196 respondents. The independent variabel was home humidity (X1), community behavior (X2), nutritional status (X3) with the dependent variable incidence of malaria. Data was collected using questionnaires and observation sheet, analysis was done by logistic regression at value of I± = 0,05. The results of the data analysis with logistic regression test can be concluded that there is the influence of moisture (p-value = 0.029 <I± = 0.05), behavior (p-value = 0.000 <I± = 0.05) and nutritional status (p-value = 0,013 <I± = 0.05) on the incidence of malaria in Umalor Village District of West Malacca NTT. This is due to malaria prevention behaviors are directly related to whether there is interaction between the respondents with mosquitoes. In accordance with the results of the research, they are ignoring what the cause of malaria and its prevention, whereas the other respondents who already know how to prevent it.

Malaria morbidity in Moru health center, with parameter Annual Parasite Incident (API), amounted to 16.9% in 2014. This figure was still high when compared to the target of eliminating malaria in Indonesia about &lt;1% in 2030. Incidence of malaria is more common in children aged 5 months - &lt;12 years. This high rates of malaria leads to poverty, low level of learning achievement of children and in pregnant women causing low birth weight in babies and death. The purpose of this study was to analyze the factors that influence the incidence of tertian and Tropikana malaria or combined Tropikana and tertian (mix) in Moru PHC in sub-district Alor Southwestern, Alor Regency.This study used a cross-sectional design, the population of study were all patients undergoing peripheral blood examination in Moru PHC’s laboratory from June to October 2015. The number of samples in this study was 173 respondents. The sampling technique was Simple Random Sampling. Instruments of data collection were a questionnaire and observation sheet.Results of the study by Chi-Square test showed that the factors influencing the incidence of malaria were socioeconomic status (sig 0,000), education level (sig 0.001). By using multivariate analysis with logistic regression test, results were obtained the age of 5 months - &lt;12 value (sig 0.025) and socioeconomic status (sig 0,000) influencing the incidence of malaria.Variables that affect the incidence of malaria were demographic factors such as age, education level, socioeconomic status. It is advisable to harness swamp thus improving the economic status of society and build permanent house.Keywords: incidence malaria, demographic factors, history of malaria

Malaria morbidity in Moru health center, with parameter Annual Parasite Incident (API), amounted to 16.9% in 2014. This figure was still high when compared to the target of eliminating malaria in Indonesia about &lt;1% in 2030. Incidence of malaria is more common in children aged 5 months - &lt;12 years. This high rates of malaria leads to poverty, low level of learning achievement of children and in pregnant women causing low birth weight in babies and death. The purpose of this study was to analyze the factors that influence the incidence of tertian and Tropikana malaria or combined Tropikana and tertian (mix) in Moru PHC in sub-district Alor Southwestern, Alor Regency.This study used a cross-sectional design, the population of study were all patients undergoing peripheral blood examination in Moru PHC’s laboratory from June to October 2015. The number of samples in this study was 173 respondents. The sampling technique was Simple Random Sampling. Instruments of data collection were a questionnaire and observation sheet.Results of the study by Chi-Square test showed that the factors influencing the incidence of malaria were socioeconomic status (sig 0,000), education level (sig 0.001). By using multivariate analysis with logistic regression test, results were obtained the age of 5 months - &lt;12 value (sig 0.025) and socioeconomic status (sig 0,000) influencing the incidence of malaria.Variables that affect the incidence of malaria were demographic factors such as age, education level, socioeconomic status. It is advisable to harness swamp thus improving the economic status of society and build permanent house.Keywords: incidence malaria, demographic factors, history of malaria

To assess the spatial distribution of TB and malaria incidence, as well as their spatial association with each other, regardless of environmental and socio-economic factors commonly reported as determinants of both disease rates among the municipalities of Amazonas State, Brazil between 2012 and 2015. Through an ecological approach considering municipalities of Amazonas, Brazil, as unit of analysis, a negative binomial regression model was used to assess association between malaria and TB rates, in which the dependent variable was the average municipal tuberculosis incidence rate. Positive associations of overall malaria (β=0.100 [CI=0.032, 0.168], P=0.004), P.vivax malaria (β=0.115 [CI=0.036, 0.195], P=0.005), and P.falciparum malaria (β=0.389 [CI=-0.0124, 0.791], P=0.057) with TB rates were found, regardless of the sociodemographic factors included in the study. In the Brazilian Amazon, TB and malaria are spatially associated. Therefore, it is very likely that co-infections also occur in this region, regardless of the HIV status.

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.

BackgroundMalaria continues to plague sub-Saharan Africa despite great efforts geared towards its mitigation. In Kenya alone, 70% of the population remains at risk for malaria every year. Malaria is spread by Anopheles mosquitoes carrying the Plasmodium parasite, and displays a complex ecology with various socio-economic, biophysical factors and meteorological predictors, particularly temperature and precipitation, associated with the occurrence of the disease.MethodsThis study estimated the empirical relationship of temperature and precipitation on the temporal population dynamics of symptomatic malaria cases in Kenyan children living in Ukunda (on Kenyan southern coast), and Kisumu (on Kenyan lake zone) between 2014 and 2022 using daily malaria incidence data collected during a febrile illness surveillance study, merged with daily climatological data collected from ground devices. Generalized additive mixed models (GAMMs) were used to explore the relationship between malaria cases and temperature and precipitation, with Poisson, zero-inflated Poisson and negative binomial distribution and a logarithmic link function. The cross-correlation function assessed the time lags with peak correlations between malaria incidence, precipitation and temperature.ResultsThe data showed 673 positive malaria incident cases amongst children in Kisumu compared to 1209 cases in Ukunda. The results indicate a positive correlation of malaria incidence with rainfall and temperature in Kisumu and a positive correlation between malaria incidence and rainfall and a negative correlation between malaria incidence and temperature in Ukunda. The lags between malaria incidence and rainfall were similar for Kisumu and Ukunda and estimated between 7 and 15 weeks. With a time lag of 15 weeks in Ukunda, GAMM depicted a steady relationship between rainfall and malaria cases until rainfall reaches 150 mm and the relationship between malaria cases and temperature peaks at 26–27 °C. In Kisumu using a time lag of 15 weeks in the GAMM, a steady relationship between rainfall and malaria cases was observed until almost 120 mm of rainfall, peaking at 160 mm of rainfall and the relationship between malaria cases and temperature remained steady between 22 and 30 °C.ConclusionAssessing the changes in malaria case incidence due to changing seasonality and weather patterns provides policymakers with updated information to strategize malaria control policies.

BackgroundThe aim of this study was to determine the incidence and seasonal pattern of malaria in children in South-West Burkina Faso, and to compare, in a randomized trial, characteristics of cases detected by active and passive surveillance. This study also enabled the planning of a malaria vaccine trial.MethodsHouseholds with young children, located within 5 kilometers of a health facility, were randomized to one of two malaria surveillance methods. In the first group, children were monitored actively. Each child was visited twice weekly; tympanic temperature was measured, and if the child had a fever or history of fever, a malaria rapid diagnostic test was performed and a blood smear collected. In the second group, children were monitored passively. The child’s parent or caregiver was asked to bring the child to the nearest clinic if he was unwell. Follow up lasted 13 months from September 2009.ResultsIncidence of malaria (Fever with parasitaemia ≥5,000/µL) was 1.18 episodes/child/year in the active cohort and 0.89 in the passive cohort (rate ratio 1.32, 95% CI 1.13–1.54). Malaria cases in the passive cohort were more likely to have high grade fever; but parasite densities were similar in the two groups. Incidence was highly seasonal; when a specific case definition was used, about 60% of cases occurred within the 4 months June-September.ConclusionPassive case detection required at least a 30%–40% increase in the sample size for vaccine trials, compared to active detection, to achieve the same power. However we did not find any evidence that parasite densities were higher with passive than with active detection. The incidence of malaria is highly seasonal and meets the WHO criteria for Seasonal Malaria Chemoprevention (SMC). At least half of the malaria cases in these children could potentially be prevented if SMC was effectively deployed.

Background: Malaria is still one of the main infectious diseases of concern in the world. Lahat Regency is a moderate malaria-endemic area in South Sumatra, where there are still several villages with an API value above 1 and indigenous cases, although the average API value in all health facilities is below 1.&#x0D; Methods: Quantitative research with a case-control design was employed. The sampling technique used stratified random sampling with year strata, namely 2018, 2019 and 2020 with 50 case respondents and 100 control respondents. The total number of samples collected was 150. Case respondents were people who suffered from malaria and are recorded in the Malaria Surveillance Information System in the working area of the community health center, which has a village with an API value of 1 and the presence of indigenous cases. Control respondents were the closest neighbours of cases with the same age characteristics as the case. This study aimed to identify and analyse risk factors for preventive behaviour related to malaria incidence in the endemic area of the Lahat Regency.&#x0D; Results: : Bivariate analysis revealed that the habit of using insect repellent was connected with the incidence of malaria in the endemic region of Lahat Regency, with a p-value of 0.042 and an odds ratio of 2.160 in the endemic area. The results of multivariate analysis showed that the most dominant risk factor was the habit of using mosquito repellent.&#x0D; Conclusions: The habit of using mosquito repellent is a risk factor for malaria incidence in endemic areas of the Lahat Regency. It is necessary to increase individual self-prevention behaviour and counselling activities regarding preventive behaviour by local health service facilities.

To provide information about preventive measures and treatment seeking behaviour as well as an estimate of the malaria burden in different epidemiological settings for effective monitoring and evaluation of the ongoing efforts. Cross-sectional survey carried out in four areas representing different levels of transmission to explore the use of preventive measures, care-seeking behaviour and accessibility in addition to point prevalence was followed by a follow-up phase in which the health workers registered and reported all fever cases including malaria. The relation between the reported malaria incidence, the product of symptomatic/asymptomatic ratio and the prevalence of confirmed malaria cases was used to develop the equation that could predict the true malaria incidence. Thousand households and 3628 individuals were surveyed. The presence of any net varied between 6.6% and 40%; the percentage of people who reportedly slept under mosquito nets in the previous night varied between 35 and 80. Prompt use of medications ranged between 14 and 48% with a delay of more than 24 h noticed in different areas. The mean number of individuals per household who reported use of anti-malarial drugs in the last 2 weeks ranged between 0.6 (SD = 0.92) and 1.2 (SD = 1.1), with variable cost per treatment and affordability. The prevalence of asymptomatic parasitaemia, fever and confirmed malaria at time of the survey differed by area. The incidence of malaria during the follow-up period was estimated to be 8.5, 178.6, 23.7 and 10.3 episodes per 1000 population in Malakal, Elrank, Elhosh and El Matama, respectively. Based on this, a prediction equation was developed. We found suboptimal health care seeking behaviour, coverage and use of preventive measures with a high malaria burden. We developed a model for future estimation of malaria episodes.

To the Editor: In Ethiopia, malaria is unstable and commonly occurs as intraannual and interannual epidemics. Transmission is associated with altitude, temperature, and rainfall, generally peaking twice a year, after the 2 rainy seasons (March–May and July–September) (1). Cases are caused by Plasmodium falciparum and P. vivax. Anopheles arabiensis mosquitoes are the main vector for both species. Although malaria is the most common communicable disease in Ethiopia (2), few longitudinal case data has been published (3). We report a retrospective analysis of outpatient data for July 2001–June 2006 obtained from all secondary and tertiary government-run health facilities (152 health centers and 25 hospitals) in Oromia Regional State. Oromia has 17 administrative zones and 297 districts. Data were reported monthly on paper forms by health facility staff at district level to the Oromia Regional Health Bureau Zonal Health Offices, which aggregated zonal data before forwarding them to the Oromia Regional Health Bureau Malaria Control Department. Data obtained included number of outpatient cases (i.e., patients attending the health facility grouped by age 5 years); number of clinical malaria cases (i.e., patients with fever grouped by age and sex); number of clinical cases confirmed by microscopy; and number of cases caused by P. falciparum and P. vivax. If no outpatient data were reported, the case number was changed from zero to missing. The data were entered into Microsoft Excel (Microsoft, Redmond, WA, USA) and analyzed by using Stata version 9.0 (StataCorp LP, College Station, TX, USA). During 2001–2006, a total of 8,786,088 outpatient consultations were reported. A total of 905,467 and 562,996 clinical and confirmed malaria cases, respectively, were reported. Patients were predominantly seen at health centers rather than at hospitals, with 80.2% clinical and 72.2% confirmed malaria cases seen at health centers. Clinical malaria accounted for 10.3% of outpatient consultations in all facilities. However, this percentage varied between years (6.1%–16.0%) and zones (1.3%–21.9%) (Technical Appendix Figure 1). Of clinical malaria cases, 16.5% were in children <5 years of age (range between years [RBY] 14.0%–18.3%, range between zones [RBZ] 10.9%–61.0%) and 54.3% were in male patients (RBY 52.2%–55.6%, RBZ 50.1%–66.8%). Of clinical malaria cases, 49.2% were confirmed by microscopy (RBY 37.1%–58.0%, RBZ 15.3%–98.4%), and 58.5% (RBY 46.4%–63.4%, RBZ 12.1%–82.4%), and 41.2% (RBY 36.3%–53.4%, RBZ 17.6%–87.9%) of confirmed cases were caused by P. falciparum and P. vivax, respectively. Of confirmed cases, 0.4% were caused by mixed Plasmodium infections (RBY 0.2%–0.5%, RBZ 0.0%–1.1%). The average incidence of clinical malaria per 100,000 population per month ranged from 14 in February 2002 to 122 in November 2003, and there was considerable variation between months, years, and administrative zones (Technical Appendix Figure 2). We found that up to 29.0% of outpatient visits to health facilities in certain administrative zones during high transmission years were for malaria. The incidence of malaria is likely to be underestimated because only ≈30% of the population accessed health facilities at that time (4). There appeared to be only 1 annual peak of transmission in September–January (Technical Appendix Figure 1). Clinical and confirmed disease varied between zones; 5 of the 15 zones in Oromia (East Hararge, East Shoa, East Wellega, Jimma, West Hararge) reported >75% of the clinical cases seen at health facilities during 2001–2006. Malaria incidence varied between years: clinical and confirmed cases increased in 2003, the last epidemic year recorded in Oromia (5), before decreasing to 2001 levels in 2004 (Technical Appendix Figure 1). The P. falciparum to P. vixax ratio changed geographically and temporally (Technical Appendix Figure 1), and increases in the proportion of P. falciparum cases coincided with the peak malaria transmission season. In the epidemic year of 2003, the proportion of P. falciparum cases was larger than in other years, and children <5 years of age were disproportionately affected (Technical Appendix Figure 1). Contrary to previous reports (6), our data did not indicate a change in the P. falciparum to P. vivax ratio after artemether/lumefantrine was introduced in 2005. Health facility data can have many caveats (7), including concerns about data representativeness (e.g., if only a small number of facilities are assessed); data validity, particularly if, as was the case during that time, only limited diagnostic quality assurance was available (8); and analytical approaches used. Our analysis comprised all Oromia secondary and tertiary facilities; only 3.4% of health centers and 13.0% of hospitals surveyed had no data, suggesting that given the extensive data reported, these missing data would have only marginally affected the temporal and spatial trends observed. Our data complement those of recent cross-sectional surveys (9) and provide a useful baseline to assess scale-up of malaria prevention and control efforts. Unlike cross-sectional and small-scale facility surveys (6), our comprehensive longitudinal monthly data monitored disease trends spatially and temporally, showing that malaria still represented a major health services problem until 2006.

BackgroundAfter the re-emergence of Plasmodium vivax in 1993, a total of 31,254 cases of vivax malaria were reported between 1993–2012 in the Republic of Korea (ROK). The purpose of this study was to review Korea Centers for Disease Control and Prevention records to investigate the transmission of malaria from 2010–2012.MethodsReporting of microscopy-diagnosed cases of malaria is mandatory in the ROK. In this study, all available records of malaria cases and malaria vectors collected from 2010 – 2012 in Cheorwon County, Gangwon Province and Ganghwa County, Incheon Metropolitan City, were reviewed.ResultsAlthough the number of cases of malaria peaked a third time in 2010 (1,772 cases) since the re-emergence of P. vivax, the incidence decreased two-fold to 838 in 2011 and three-fold to 555 in 2012. The number of cases decreased 52.7% in 2011 compared with that in 2010 and 33.8% in 2012 compared with that in 2011. However, the number of cases increased in Incheon Metropolitan City (15.3%) and Gyeongnam Province (23.1%) in 2012 compared with 2011. Of the 3,165 cases of vivax malaria in 2010–2012, 798 (25.2%) were in ROK military personnel, 519 (16.4%) in veterans, and 1,848 (58.4%) in civilians. In total, there were 2,666 male patients and 499 female patients, and the ratio of female to male patients increased from 1:7.9 in 2011 to 1:4.1 in 2012.ConclusionsA rapid decrease in the incidence of malaria was observed in most areas from 2010 to 2012, but the incidence increased again in the western part of the demilitarized zone. Therefore, more intensive surveillance is needed throughout high risk areas to identify factors responsible for increase/decrease in the incidence of malaria in the ROK.

A favorable climatic condition for transmission of malaria prevails in Kokrajhar district throughout the year. A sizeable part of the district is covered by forest due to which dissimilar dynamics of malaria transmission emerge in forest and non-forest areas. Observed malaria incidence rates of forest area, non-forest area and the whole district over the period 2001-2010 were considered for analyzing temporal correlation between malaria incidence and climatic variables. Associations between the two were examined by Pearson correlation analysis. Cross-correlation tests were performed between pre-whitened series of climatic variable and malaria series. Linear regressions were used to obtain linear relationships between climatic factors and malaria incidence, while weighted least squares regression was used to construct models for explaining and estimating malaria incidence rates. Annual concentration of malaria incidence was analyzed by Markham technique by obtaining seasonal index. Forest area and non-forest area have distinguishable malaria seasons. Relative humidity was positively correlated with z malaria incidence, while temperature series were negatively correlated with non-forest malaria incidence.There was higher seasonality of concentration of malaria in the forest area than non-forest area. Significant correlation between annual changes in malaria cases in forest area and temperature was observed (coeff=0.689, p=0.040).Separate reliable models constructed for forecasting malaria incidence rates based on the combined influence of climatic variables on malaria incidence in different areas of the district were able to explain substantial percentage of observed variability in the incidence rates (R2adj=45.4%, 50.6%, 47.2%; p< .001 for all). There is an intricate association between climatic variables and malaria incidence of the district. Climatic variables influence malaria incidence in forest area and non-forest area in different ways. Rainfall plays a primary role in characterizing malaria incidences in the district. Malaria parasites in the district had adapted to a relative humidity condition higher than the normal range for transmission in India. Instead of individual influence of the climatic variables, their combined influence was utilizable for construction of models.

Malaria remains a public health challenge in sub-Saharan Africa. In response to this, many countries are working towardsachieving the World Health Assembly and Roll Back Malaria Partnership target of a 75% decline in malaria incidence. To assess trends in malaria morbidity and mortality in the three islands of the Comoros Archipelago from 2010 to 2014. This was a retrospective study in which all confirmed malaria cases and deaths recorded between 2010 and 2014 were accessedfrom the national malaria control database. Trends and comparisons in malaria incidence and case fatality rates for all age groups, includingunder-5 children and pregnant women, were analysed using Microsoft Excel and SPSS version 16. A substantial decline in malaria incidence was observed for each island between 2010 and 2014; from 75.98 cases per 1 000 populationin 2010 to 0.14 in 2014 in Moheli, 60.60 to 0.02 in Anjouan and 235.36 to 5.47 in Grand Comoro. Additionally, a general reduction in malariacase fatalities was observed. In Moheli, there were no case fatalities between 2010 and 2014, while there was a decline in the case fatality rate inAnjouan (from 1.20 fatalities per 1 000 cases to 0) and Grand Comoros (0.51 to 0). There were also significant differences (p&lt;0.05) in malariaincidence and case fatalities between the three islands. A similar trend was observed for pregnant women and under-5 children. Our study indicates a significant decline in malaria morbidity and mortality in the islands of Moheli, Anjouan and GrandComoro from 2010 to 2014. This considerable reduction is attributed to a combination of malaria prevention and control interventionsimplemented during the study period.

Malaria remains a significant public health issue both globally and in Indonesia, particularly affecting high-risk groups such as infants, young children, and pregnant women. The increasing incidence of malaria is closely linked to environmental and behavioral factors. This study aims to examine the relationship between community behavior and environmental conditions with malaria incidence at the Arso City Health Center, Keerom Regency. A quantitative, cross-sectional design was used, allowing analysis of variables at a single point in time. The sample was selected through simple random sampling based on inclusion and exclusion criteria. Findings revealed that there is no significant relationship between the habit of going outside the house and malaria incidence (p = 0.07). However, there is a significant relationship between the use of mosquito repellent and malaria incidence (p = 0.000). Similarly, using mosquito nets and gauze also showed a significant relationship with reduced malaria cases. Environmental aspects such as mosquito breeding sites and unsealed house walls were also found to be significantly associated with malaria occurrence. These results suggest that both behavioral factors—particularly protective measures—and environmental conditions contribute to malaria transmission in the community. Public health efforts should prioritize education on preventive behaviors and improvements in living environments to reduce malaria risk.

Effects of spraying the mosquito biolarvicides Bacillus thuringiensisvar. israelensis(Bti) and Bacillus sphaericus(Bs) over freshwater bodies in four selected areas of Lusaka urban district, on incidences of malaria in the areas were investigated. Incidences of malaria prior to and after larviciding of the study areas were determined by reviewing and analyzing health centre records of laboratory confirmed positive malaria cases in the study areas prior to and after larviciding. There were relatively higher incidences of malaria cases in all study areas prior to larviciding. Malaria cases dropped drastically by 53-72 % immediately after larviciding in all study areas. However, though numerically very small percent-wise, there were observed marked rises in incidences of positive diagnosed malaria cases in Chelstone study area by the second month. Three study areas; Chainda, Mtendere and Ng'ombe showed continued decline or had slight rises in the incidences of malaria two months after larviciding. Possible reasons for the observed slight rises in incidence in the areas were; importation of malaria by travelers from outside the Lusaka urban district. The deployment of Bti and Bs larvicides in the context of integrated vector management is likely to have long term impacts on incidences of malaria in Zambia.