Lack of Consistent Malaria Incidence Hotspots in a Highland Kenyan Area During a 10-Year Period of Very Low and Unstable Transmission

Malaria still becomes a public health problem in Indonesia although has declined the last decades. The incidences of malaria in Banyumas shows unstable transmission and still risk of epidemic . Thus, the spatial and temporal distribution is required as part of efforts towards the elimination of malaria in Banyumas. Temporal spatial statistical methods is used to identify a group of malaria incidence at the district level. Purely spatial clusters of malaria incidence from 2004 to 2015 shows that the disease is not distributed randomly in the study area. A total of nine districts of high risk is determined by analysis of Morans I. The analysis showed that by the Morans I test, there is spatial autocorrelation found in the percentage malaria incidence from 2004 to 2015 in Banyumas. The use of the model can provide a means to detect the spatial distribution, temporal, and spatiotemporal malaria, as well as to identify areas of high risk of malaria. This research may help in prioritizing resources on high-risk areas for malaria control in the future and towards the elimination of malaria in Banyumas.

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

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17176339 ◽

2020 ◽

Vol 17 (17) ◽

pp. 6339

Author(s):

François Freddy Ateba ◽

Manuel Febrero-Bande ◽

Issaka Sagara ◽

Nafomon Sogoba ◽

Mahamoudou Touré ◽

...

Keyword(s):

Wind Speed ◽

Malaria Incidence ◽

Generalized Additive Models ◽

Community Health Center ◽

Additive Model ◽

Additive Models ◽

Functional Regression ◽

Novel Approach ◽

Malaria Incidence Rate ◽

Mean Wind Speed

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.

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Malaria rapid diagnostic test (HRP2/pLDH) positivity, incidence, care accessibility and impact of community WASH Action programme in DR Congo: mixed method study involving 625 households

Malaria Journal ◽

10.1186/s12936-021-03647-9 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Nlandu Roger Ngatu ◽

Basilua Andre Muzembo ◽

Nattadech Choomplang ◽

Sakiko Kanbara ◽

Roger Wumba ◽

...

Keyword(s):

Action Research ◽

Diagnostic Test ◽

Rapid Diagnostic Test ◽

Mixed Method ◽

Malaria Incidence ◽

Control Site ◽

Malaria Rapid Diagnostic Test ◽

Post Intervention ◽

Referral Hospitals ◽

Action Programme

Abstract Background Malaria is one of the most prevalent and deadliest illnesses in sub-Saharan Africa. Despite recent gains made towards its control, many African countries still have endemic malaria transmission. This study aimed to assess malaria burden at household level in Kongo central province, Democratic Republic of Congo (DRC), and the impact of community participatory Water, Sanitation and Hygiene (WASH) Action programme. Methods Mixed method research was conducted in two semi-rural towns, Mbanza-Ngungu (a WASH action site) and Kasangulu (a WASH control site) in DRC between 1 January 2017 through March 2018, involving 625 households (3,712 household members). Baseline and post-intervention malaria surveys were conducted with the use of World Bank/WHO Malaria Indicator Questionnaire. An action research consisting of a six-month study was carried out which comprised two interventions: a community participatory WASH action programme aiming at eliminating mosquito breeding areas in the residential environment and a community anti-malaria education campaign. The latter was implemented at both study sites. In addition, baseline and post-intervention malaria rapid diagnostic test (RDT) was performed among the respondents. Furthermore, a six-month hospital-based epidemiological study was conducted at selected referral hospitals at each site from 1 January through June 2017 to determine malaria trend. Results Long-lasting insecticide-treated net (LLIN) was the most commonly used preventive measure (55%); 24% of households did not use any measures. Baseline malaria survey showed that 96% of respondents (heads of households) reported at least one episode occurring in the previous six months; of them only 66.5% received malaria care at a health setting. In the Action Research, mean incident household malaria cases decreased significantly at WASH action site (2.3 ± 2.2 cases vs. 1.2 ± 0.7 cases, respectively; p < 0.05), whereas it remained unchanged at the Control site. Similar findings were observed with RDT results. Data collected from referral hospitals showed high malaria incidence rate, 67.4%. Low household income (ORa = 2.37; 95%CI: 1.05–3.12; p < 0.05), proximity to high risk area for malaria (ORa = 5.13; 95%CI: 2–29-8.07; p < 0.001), poor WASH (ORa = 4.10; 95%CI: 2.11–7.08; p < 0.001) were predictors of household malaria. Conclusion This research showed high prevalence of positive malaria RDT among the responders and high household malaria incidence, which were reduced by a 6-month WASH intervention. DRC government should scale up malaria control strategy by integrating efficient indoor and outdoor preventive measures and improve malaria care accessibility.

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Short-Time Recurrences of Plasmodium vivax Malaria as a Public Health Proxy for Chloroquine-Resistance Surveillance: A Spatio-Temporal Study in the Brazilian Amazon

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18105061 ◽

2021 ◽

Vol 18 (10) ◽

pp. 5061

Author(s):

Antonio A. S. Balieiro ◽

Andre M. Siqueira ◽

Gisely C. Melo ◽

Wuelton M. Monteiro ◽

Vanderson S. Sampaio ◽

...

Keyword(s):

Plasmodium Vivax ◽

Multilevel Models ◽

Malaria Incidence ◽

Chloroquine Resistance ◽

Spatial Clusters ◽

Temporal Study ◽

Plasmodium Vivax Malaria ◽

Spatio Temporal ◽

Spatially Varying ◽

Short Time

In Brazil, malaria caused by Plasmodium vivax presents control challenges due to several reasons, among them the increasing possibility of failure of P. vivax treatment due to chloroquine-resistance (CQR). Despite limited reports of CQR, more extensive studies on the actual magnitude of resistance are still needed. Short-time recurrences of malaria cases were analyzed in different transmission scenarios over three years (2005, 2010, and 2015), selected according to malaria incidence. Multilevel models (binomial) were used to evaluate association of short-time recurrences with variables such as age. The zero-inflated Poisson scan model (scanZIP) was used to detect spatial clusters of recurrences up to 28 days. Recurrences compose less than 5% of overall infection, being more frequent in the age group under four years. Recurrences slightly increased incidence. No fixed clusters were detected throughout the period, although there are clustering sites, spatially varying over the years. This is the most extensive analysis of short-time recurrences worldwide which addresses the occurrence of P. vivax CQR. As an important step forward in malaria elimination, policymakers should focus their efforts on young children, with an eventual shift in the first line of malaria treatment to P. vivax.

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Relationships between test positivity rate, total laboratory confirmed cases of malaria, and malaria incidence in high burden settings of Uganda: an ecological analysis

Malaria Journal ◽

10.1186/s12936-021-03584-7 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Jaffer Okiring ◽

Adrienne Epstein ◽

Jane F. Namuganga ◽

Victor Kamya ◽

Asadu Sserwanga ◽

...

Keyword(s):

Regression Models ◽

Malaria Incidence ◽

Temporal Changes ◽

Linear Regression Models ◽

High Burden ◽

Exponential Regression ◽

Malaria Morbidity ◽

Laboratory Test Results ◽

Combining Data ◽

Catchment Areas

Abstract Background Malaria surveillance is critical for monitoring changes in malaria morbidity over time. National Malaria Control Programmes often rely on surrogate measures of malaria incidence, including the test positivity rate (TPR) and total laboratory confirmed cases of malaria (TCM), to monitor trends in malaria morbidity. However, there are limited data on the accuracy of TPR and TCM for predicting temporal changes in malaria incidence, especially in high burden settings. Methods This study leveraged data from 5 malaria reference centres (MRCs) located in high burden settings over a 15-month period from November 2018 through January 2020 as part of an enhanced health facility-based surveillance system established in Uganda. Individual level data were collected from all outpatients including demographics, laboratory test results, and village of residence. Estimates of malaria incidence were derived from catchment areas around the MRCs. Temporal relationships between monthly aggregate measures of TPR and TCM relative to estimates of malaria incidence were examined using linear and exponential regression models. Results A total of 149,739 outpatient visits to the 5 MRCs were recorded. Overall, malaria was suspected in 73.4% of visits, 99.1% of patients with suspected malaria received a diagnostic test, and 69.7% of those tested for malaria were positive. Temporal correlations between monthly measures of TPR and malaria incidence using linear and exponential regression models were relatively poor, with small changes in TPR frequently associated with large changes in malaria incidence. Linear regression models of temporal changes in TCM provided the most parsimonious and accurate predictor of changes in malaria incidence, with adjusted R2 values ranging from 0.81 to 0.98 across the 5 MRCs. However, the slope of the regression lines indicating the change in malaria incidence per unit change in TCM varied from 0.57 to 2.13 across the 5 MRCs, and when combining data across all 5 sites, the R2 value reduced to 0.38. Conclusions In high malaria burden areas of Uganda, site-specific temporal changes in TCM had a strong linear relationship with malaria incidence and were a more useful metric than TPR. However, caution should be taken when comparing changes in TCM across sites.

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Estimating the local spatio‐temporal distribution of malaria from routine health information systems in areas of low health care access and reporting

International Journal of Health Geographics ◽

10.1186/s12942-021-00262-4 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Elizabeth Hyde ◽

Matthew H. Bonds ◽

Felana A. Ihantamalala ◽

Ann C. Miller ◽

Laura F. Cordier ◽

...

Keyword(s):

Health Care ◽

Access To Health Care ◽

Malaria Incidence ◽

Universal Access ◽

Surveillance Systems ◽

Passive Surveillance ◽

Transmission Season ◽

Access To Health ◽

Spatio Temporal ◽

Geographic Access To Care

Abstract Background Reliable surveillance systems are essential for identifying disease outbreaks and allocating resources to ensure universal access to diagnostics and treatment for endemic diseases. Yet, most countries with high disease burdens rely entirely on facility-based passive surveillance systems, which miss the vast majority of cases in rural settings with low access to health care. This is especially true for malaria, for which the World Health Organization estimates that routine surveillance detects only 14% of global cases. The goal of this study was to develop a novel method to obtain accurate estimates of disease spatio-temporal incidence at very local scales from routine passive surveillance, less biased by populations' financial and geographic access to care. Methods We use a geographically explicit dataset with residences of the 73,022 malaria cases confirmed at health centers in the Ifanadiana District in Madagascar from 2014 to 2017. Malaria incidence was adjusted to account for underreporting due to stock-outs of rapid diagnostic tests and variable access to healthcare. A benchmark multiplier was combined with a health care utilization index obtained from statistical models of non-malaria patients. Variations to the multiplier and several strategies for pooling neighboring communities together were explored to allow for fine-tuning of the final estimates. Separate analyses were carried out for individuals of all ages and for children under five. Cross-validation criteria were developed based on overall incidence, trends in financial and geographical access to health care, and consistency with geographic distribution in a district-representative cohort. The most plausible sets of estimates were then identified based on these criteria. Results Passive surveillance was estimated to have missed about 4 in every 5 malaria cases among all individuals and 2 out of every 3 cases among children under five. Adjusted malaria estimates were less biased by differences in populations’ financial and geographic access to care. Average adjusted monthly malaria incidence was nearly four times higher during the high transmission season than during the low transmission season. By gathering patient-level data and removing systematic biases in the dataset, the spatial resolution of passive malaria surveillance was improved over ten-fold. Geographic distribution in the adjusted dataset revealed high transmission clusters in low elevation areas in the northeast and southeast of the district that were stable across seasons and transmission years. Conclusions Understanding local disease dynamics from routine passive surveillance data can be a key step towards achieving universal access to diagnostics and treatment. Methods presented here could be scaled-up thanks to the increasing availability of e-health disease surveillance platforms for malaria and other diseases across the developing world.

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The malaria burden of Amerindian groups of three Venezuelan states: a descriptive study based on programmatic data

Malaria Journal ◽

10.1186/s12936-021-03819-7 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Juan C. Gabaldón-Figueira ◽

Carlos Chaccour ◽

Jorge Moreno ◽

Maria Villegas ◽

Leopoldo Villegas

Keyword(s):

Risk Factors ◽

Plasmodium Falciparum ◽

Malaria Incidence ◽

Hot Spot ◽

Public Health Problem ◽

Epidemiological Data ◽

Descriptive Study ◽

Malaria Burden ◽

Indigenous Groups ◽

The Impact

Abstract Background Fifty-three percent of all cases of malaria in the Americas in 2019 came from Venezuela, where the epidemic is heavily focused south of the Orinoco river, and where most of the country’s Amerindian groups live. Although the disease is known to represent a significant public health problem among these populations, little epidemiological data exists on the subject. This study aims to provide information on malaria incidence, geospatial clustering, and risk factors associated to Plasmodium falciparum infection among these groups. Methods This is a descriptive study based on the analysis of published and unpublished programmatic data collected by Venezuelan health authorities and non-government organizations between 2014 and 2018. The Annual Parasite Index among indigenous groups (API-i) in municipalities of three states (Amazonas, Bolivar, and Sucre) were calculated and compared using the Kruskal Wallis test, risk factors for Plasmodium falciparum infection were identified via binomial logistic regression and maps were constructed to identify clusters of malaria cases among indigenous patients via Moran’s I and Getis-Ord’s hot spot analysis. Results 116,097 cases of malaria in Amerindian groups were registered during the study period. An increasing trend was observed between 2014 and 2016 but reverted in 2018. Malaria incidence remains higher than in 2014 and hot spots were identified in the three states, although more importantly in the south of Bolivar. Most cases (73.3%) were caused by Plasmodium vivax, but the Hoti, Yanomami, and Eñepa indigenous groups presented higher odds for infection with Plasmodium falciparum. Conclusion Malaria cases among Amerindian populations increased between 2014 and 2018 and seem to have a different geographic distribution than those among the general population. These findings suggest that tailored interventions will be necessary to curb the impact of malaria transmission in these groups.

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Modelling the impact of rapid diagnostic tests on Plasmodium vivax malaria in South Korea: a cost–benefit analysis

BMJ Global Health ◽

10.1136/bmjgh-2020-004292 ◽

2021 ◽

Vol 6 (2) ◽

pp. e004292

Author(s):

Jung Ho Kim ◽

Jiyeon Suh ◽

Woon Ji Lee ◽

Heun Choi ◽

Jong-Dae Kim ◽

...

Keyword(s):

South Korea ◽

Plasmodium Vivax ◽

Diagnostic Tests ◽

Cost Benefit Analysis ◽

Malaria Incidence ◽

Cost Benefit ◽

Medical Costs ◽

Rapid Diagnostic Tests ◽

Benefit Analysis ◽

The Impact

BackgroundRapid diagnostic tests (RDTs) are widely used for diagnosing Plasmodium vivax malaria, especially in resource-limited countries. However, the impact of RDTs on P. vivax malaria incidence and national medical costs has not been evaluated. We assessed the impact of RDT implementation on P. vivax malaria incidence and overall medical expenditures in South Korea and performed a cost–benefit analysis from the payer’s perspective.MethodsWe developed a dynamic compartmental model for P. vivax malaria transmission in South Korea using delay differential equations. Long latency and seasonality were incorporated into the model, which was calibrated to civilian malaria incidences during 2014–2018. We then estimated averted malaria cases and total medical costs from two diagnostic scenarios: microscopy only and both microscopy and RDTs. Medical costs were extracted based on data from a hospital in an at-risk area for P. vivax malaria and were validated using Health Insurance Review and Assessment Service data. We conducted a cost–benefit analysis of RDTs using the incremental benefit:cost ratio (IBCR) considering only medical costs and performed a probabilistic sensitivity analysis to reflect the uncertainties of model parameters, costs and benefits.ResultsThe results showed that 55.3% of new P. vivax malaria cases were averted, and $696 214 in medical costs was saved over 10 years after RDT introduction. The estimated IBCR was 2.5, indicating that RDT implementation was beneficial, compared with microscopy alone. The IBCR was sensitive to the diagnosis time reduction, infectious period and short latency period, and provided beneficial results in a benefit over $10.6 or RDT cost under $39.7.ConclusionsThe model simulation suggested that RDTs could significantly reduce P. vivax malaria incidence and medical costs. Moreover, cost–benefit analysis demonstrated that the introduction of RDTs was beneficial over microscopy alone. These results support the need for widespread adoption of RDTs.

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