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

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

Five-year Surveillance of Malaria in Hotspot and Ivermectin Mass-drug Administration Zone of Amhara Regional State, Ethiopia

Objectives: Evaluate the five-year surveillance of malaria in the hotspot and Ivermectin mass-drug administration Zone of Amhara Regional State, Ethiopia.Methods: - A descriptive prevalence study design was employed and incorporated 25 study health institutions into the survey using the purposive sampling technique. Data were obtained by the standard format of systematic evaluation of four surveillance units from January to August 2020 through observation, document review, and interviewing surveillance officers and focal persons using a semi-structured Survey and generated the statistical analysis, tabular, and graphical output using the open-source statistical program R. Results: - Average report fullness and aptness were 97.9% and 96% subsequently. The average annual malaria incidence rate declined in terms of place and time, from the year 2015 to 2019 with an average reduction rate of 5.5% and the average annual parasitic incidence rate was 52%. The study identifies high endemicity of malaria due to no program-specific supportive supervision of public health emergency management and no routine data analysis.Conclusions: This result revealed that the malaria incidence rate showed a remarkable decline. However, the annual parasitic incidence rate remains constant. The study also indicated that ivermectin did not affect malaria elimination. Hence, the districts and sub-city health offices should conduct regular surveillance data analysis, perform supportive supervision, avail budgets, and further laboratory investigations to investigate the effect of ivermectin on the parasites under laboratory conditions.

The Impact of Meteorological Parameters on the Pattern of Malaria Incidence Rate in the Northwest, Ethiopia; Repeated Cross-sectional Study Design With Bayesian Approach

Background: Commonly the incidence of malaria was determined by some meteorological parameters. However, updated evidences were not reported in the study area and recently malaria is reported as an epidemic disease in Ethiopia particularly in Amhara regional state. Therefore the study was aimed to estimate malaria incidence proportion linked with some meteorological parameters.Methods: A repeated cross-sectional study design was done in 8 districts of northwest Ethiopia. All malaria patients who visited the local health institutions in the study area were the study participants. A monthly malaria surveillance data were retrieved from 8 districts of North Gondar zone health department and metrological data were obtained from west Amhara metrology agency office monthly reported databases. Data was clean and analyzed by using R2 win bugs software. The bayesian generalized negative binomial regression model was fitted for parameter estimation. Results: The overall average cumulative annual malaria incidence rate during the study period was 29.9 per 100 populations. In this study relative humidity (IRR; 1.04 (95% BCI, 1.01-1.05), normalized difference vegetation index [IRR; 2.74(95% BCI, 1.35-5.58)], altitude [IRR; 0.97(95% BCI, 0.95 - 0.99], average maximum temperature [IRR; 1.07(95% BCI (1.05 - 1.09)] and average minimum temperature [IRR; 1.04 (95% BCI (1.02-1.07)] were the statistically significant predictors. However, monthly rainfall, length of a sunshine hour, monthly wind speed was not associated with malaria incidence. Conclusion: The research showed a greater incidence of malaria in the study area when compared to the national statistics. Climatic variability changes the pattern of the malaria incidence in the study area.

Potency of Solid Lipid Nanoparticle (SLN)-Modified Luteolin-based Polyethylene Glycol (PEG) on Allium fistulosum as Innovation Therapy of Malaria Falciparum

In 2013, 198 million cases of malaria were reported globally and 584,000 of them died. As much as 78% of cases occurred in children under five years of age. Indonesia is a has the second highest malaria incidence rate after India in the Asian region. Severe malaria can be characterized by the presence of severe anaemia, hyperparasitemia or cerebral malaria. Severe anaemia due to malaria or severe malaria anaemia (SMA) often occurs in children who suffer from falciparum malaria. SMA occurs due to a decrease in COX-2-PGE2, caused by phagocytosis of PfHz (Plasmodium falcyiparum-derived Hemozoin) by monocytes, macrophages and neutrophils. PfHz is a crystalline compound formed from the aggregation of heme hosts. Fe2+ is one of the constituents of heme, luteolin can bind Fe2+ so that the bond between luteolin and Fe2+ in heme prevents the formation of PfHz, so that severe anaemia can be prevented. Like other naturally occurring active compounds, luteolin has low bioavailability in the body so it is encapsulated using Solid Lipid Nanoparticles (SLN) and Polyethylene Glycol (PEG). SLN is useful for increasing the bioavailability of luteolin in the body, while PEG is useful for preventing the destruction of luteolin-SLN by RES. The modified construction process includes the following steps: (1) luteolin extraction from Allium fistulosum and (2) luteolin encapsulation using SLN-PEG. The potential dose to be administered orally to humans is 2.43–8.11 µg/kg body weight. Keywords: luteolin, polyethylene glycol, severe malaria anaemia, solid lipid nanoparticles

Age-related Changes in Malaria Clinical Phenotypes During Infancy are Modified by Sickle Cell Trait

Background Young infants are protected against Plasmodium falciparum malaria. Mechanisms driving this protection remain unclear due to a poor understanding of malaria clinical phenotypes during infancy. Methods We enrolled a birth cohort of 678 infants in Busia, Uganda, an area of high malaria transmission. We followed infants through 12 months of age, and quantified protection against parasitemia and clinical disease. Results Symptomatic malaria incidence increased from 1.2 to 2.6 episodes per person year between 0-&lt;6 months and 6-12 months of age, while the monthly probability of asymptomatic parasitemia given infection decreased from 32% to 21%. Sickle cell trait (HbAS) was protective against symptomatic malaria (incidence rate ratio (IRR) = 0.57 comparing HbAS vs. HbAA, 95% CI 0.44-0.74, p&lt;0.001), but age modified this relationship (Pint=&lt;0.001), with non-linear protection that waned between 0-9 months of age before increasing. Increasing age was associated with higher parasite densities at the time of infection, and, in infants with HbAS, a reduced ability to tolerate high parasite densities without fever. Conclusions Age-dependent changes in HbAS protective efficacy in infancy were accompanied by differential loss of anti-parasite and anti-disease protection among HbAS and HbAA infants. This provides a framework for investigating mechanisms underlying infant protection against malaria.

A Bayesian spatio-temporal analysis of malaria in the Greater Accra Region of Ghana from 2015 to 2019.

Efforts towards malaria control in Ghana have had positive impacts. However, these efforts need to be locally tailored to further accelerate progress. The aim of this study was to examine the climatic drivers of malaria transmission in the Greater Accra Region and identify inter-district variation of 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 the seasonal-trend decomposition, based on locally weighted regression to analyse the seasonality. A Poisson 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 was recorded in the region from 2015–2019. The overall malaria incidence rate for the region was approximately 1 per 1,000,000 population. Malaria transmission was highly seasonal with an irregular inter-annual pattern. Malaria incidence was found to increase by 0.1% (95% credible interval [CrI]: 0.02–0.16%) for a 1°C rise in monthly maximum temperature lagged at 6 months and 0.2% (95% CrI: 0.5–0.3%) for 1°C rise in monthly minimum temperature without lag. No spatial dependency was observed after accounting for climatic variables. Only five districts located in the south-central part of the region had a malaria incidence rate that was 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.

Melt-Spun Poly(D,L-lactic acid) Monofilaments Containing N,N-Diethyl-3-methylbenzamide as Mosquito Repellent

Malaria is still a major tropical disease, with Africa particularly burdened. It has been proposed that outdoor protection could aid substantially in reducing the malaria incidence rate in rural African communities. Recently, melt-spun polyolefin fibers containing mosquito repellents have been shown to be promising materials to this end. In this study, the incorporation of N,N‑Diethyl‑3‑methylbenzamide (DEET)—a popular and widely available mosquito repellent—in commercially available, amorphous poly(D,L-lactic acid) (PDLLA) is investigated with the aim of producing biodegradable mosquito-repelling filaments with a reduced environmental impact. It is shown to be possible to produce macroscopically stable PDLLA-DEET compounds containing up to 20 wt.-% DEET that can be melt-spun to produce filaments, albeit at relatively low take-up speeds. A critical DEET content allows for stress-induced crystallization during the spinning of the otherwise amorphous PDLLA, resulting in the formation of α-crystals. Although the mechanical integrity of the filaments is notably impacted by the incorporation of DEET, these filaments show potential as materials that can be used for Malaria vector control.

A Bayesian spatio-temporal analysis of malaria in the Greater Accra Region of Ghana from 2015 to 2019.

Background: Efforts towards malaria control in Ghana have had positive impacts. However, these efforts need to be locally tailored to further accelerate progress. The aim of this study was to examine the climatic drivers of malaria transmission in the Greater Accra Region and identify inter-district variation of malaria burden.Methodology: Monthly malaria cases for the Greater Accra Region were obtained from the Ghanaian District Health Information and Management System from 2015 to 2019. Malaria cases were decomposed using the seasonal-trend decomposition, based on locally weighted regression to analyze the seasonality. A Poisson 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.Results: A total of 1,105,370 malaria cases was recorded in the region from 2015–2019. The overall malaria incidence rate for the region was approximately 1 per 1,000,000 population. Malaria transmission was highly seasonal with an irregular inter-annual pattern during the study period. Malaria incidence was found to increase by 0.1% (95% credible interval [CrI]: 0.02–0.16%) for a 1°C rise in monthly mean maximum temperature lagged at 6 months and 0.2% (95% CrI: 0.5–0.3%) for 1°C rise in monthly mean minimum temperature without lag. No spatial dependency was observed after accounting for climatic variables. Only five districts located in the south-central part of the region had a malaria incidence rate that was lower than the regional average at > 95% probability level.Conclusion: 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.

Trends of Malaria on Hotspot and Ivermectin Mass-drug Administration Zone of Amhara Regional State, 2020

Background:- Public health surveillance (PHS) is the continuing organized gathering, investigation, elucidation, and well-timed distribution of health-related information for activities and program evaluation. Conducting a surveillance system evaluation is crucial for monitoring the efficacy and effectiveness of intervention programs in health care systems. This study aimed to Evaluate the Trends of Malaria in the hotspot and Ivermectin mass-drug administration Zone of Amhara Regional State, Ethiopia, 2020.Methods: - A descriptive prevalence study design was used to evaluate the surveillance system of the Awi zone selected woreda. 25 study sources were incorporated in the survey (5 District Health Offices (5HOs), 10 Health Centers (10HCs), and 10 Health Posts (10 HPs). Purposive sampling techniques were utilized. Data were obtained by communicable diseases control the standard format of systematic evaluation of four surveillance units from January to August 2020 through observation, document review, and interviewing surveillance officers and focal persons using a semi-structured Survey.Results: - Average report fullness and aptness were 97.9% and 96% respectively. The average annual malaria incidence rate was a decline from the year 2015 to 2019 with an average reduction rate of 5.5% and the average annual parasitic incidence rate was 52 (22-199). In 2019/2020, 43131 Malaria cases were reported in the zone. Supervisions were made as integrated supportive supervision in the last six months. However, there was no program specific supportive supervision of public health emergency management. Data analysis was not routinely practiced in both visited districts and was not used for decision making.Conclusions: This result revealed that the malaria incidence rate showed a remarkable decline. However, the annual parasitic incidence rate remains constant. This indicates that ivermectin did not affect malaria elimination. The structure of the surveillance information transfer as of Kebel to Zone was well organized. However, coordination and supervision of the surveillanc activities were not frequent. From those supervised health facilities, most of them are not receiving feedback. There was no budget line, written feedback, epidemic and preparedness, and a response plan regular based on supportive supervision at all visited health facilities. Depending on this, we recommend that districts and sub-city health offices should conduct regular surveillance data analysis, perform supportive supervision, avail budgets and mitigate resource constraints and improve data quality on the job training and supportive supervision. Further laboratory investigations should be done to investigate the effect of ivermectin on the parasites under laboratory conditions.

Predicting Malaria Transmission Dynamics in Dangassa, Mali: A Novel Approach Using Functional Generalized Additive Models

Mali aims to reach the pre-elimination stage of malaria by the next decade. This study used functional regression models to predict the incidence of malaria as a function of past meteorological patterns to better prevent and to act proactively against impending malaria outbreaks. All data were collected over a five-year period (2012–2017) from 1400 persons who sought treatment at Dangassa’s community health center. Rainfall, temperature, humidity, and wind speed variables were collected. Functional Generalized Spectral Additive Model (FGSAM), Functional Generalized Linear Model (FGLM), and Functional Generalized Kernel Additive Model (FGKAM) were used to predict malaria incidence as a function of the pattern of meteorological indicators over a continuum of the 18 weeks preceding the week of interest. Their respective outcomes were compared in terms of predictive abilities. The results showed that (1) the highest malaria incidence rate occurred in the village 10 to 12 weeks after we observed a pattern of air humidity levels >65%, combined with two or more consecutive rain episodes and a mean wind speed <1.8 m/s; (2) among the three models, the FGLM obtained the best results in terms of prediction; and (3) FGSAM was shown to be a good compromise between FGLM and FGKAM in terms of flexibility and simplicity. The models showed that some meteorological conditions may provide a basis for detection of future outbreaks of malaria. The models developed in this paper are useful for implementing preventive strategies using past meteorological and past malaria incidence.