Spatiotemporal clustering of malaria in southern-central Ethiopia: A community-based cohort study

Insecticide-treated bed nets and residual indoor spraying reduce malaria in areas with low transmission: a reanalysis of the Maltrials study

BACKGROUND

The malaria incidence data from a malaria prevention study from the Rift Valley, Central Ethiopia, were reanalysed. The objective was to investigate whether including an administrative structure within the society, which may have required consideration in the protocol or previous analysis, would provide divergent outcomes on the effect measures of the interventions.

METHODS

A cluster-randomized controlled trial lasting 121 weeks with 176 clusters in four groups with 6071 households with 34,548 persons was done: interventions combining indoor residual spraying (IRS) and insecticide-treated nets (ITNs), IRS alone, ITNs alone and routine use. The primary outcome was malaria incidence. A multilevel negative binomial regression model was employed to examine the impact of the kebele (smallest administrative unit) and the proximity of homes to the primary mosquito breeding sites as potential residual confounders (levels). The study also assessed whether these factors influenced the effect measures of the interventions.

RESULTS

The study's initial findings revealed 1183 malaria episodes among 1059 persons, with comparable effects observed across the four intervention groups. In the reanalysis, the results showed that both ITN + IRS (incidence rate ratio [IRR] 0.63, P < 0.001) and ITN alone (IRR 0.78, P = 0.011) were associated with a greater reduction in malaria cases compared to IRS (IRR 0.90; P = 0.28) or the control (reference) group. The combined usage of IRS with ITN yields better outcomes compared to the standalone use of ITN and surpasses the effectiveness of IRS in isolation.

CONCLUSION

The findings indicate that implementing a combination of IRS and ITN and also ITN alone decrease malaria incidence. Furthermore, there was an observed synergistic impact when ITN and IRS were used in combination. Considering relevant social structures as potential residual confounders is of paramount importance.

TRIAL REGISTRATION

PACTR201411000882128 (08 September 2014).

Insecticide treated eaves screens provide additional marginal protection compared to untreated eave screens under semi-field conditions in western Kenya

Introduction

Human habitats remain the main point of human-vector interaction leading to malaria transmission despite the sustained use of insecticide-treated nets and indoor residual spraying. Simple structural modifications involving screening of doors, windows and eaves have great potential for reducing indoor entry of mosquitoes. Moreover, insecticide treatment of the screen material may provide additional benefit in mosquito population reduction.

Materials and Methods

Four huts, each constructed inside a semi-field structure, were used in the study. Two had untreated eave and door screens and screened air cavities in place of windows (experiment 1) or were similar but with the eave screens treated with Actellic® 300CS insecticide (experiment 2). The other two huts remained unscreened throughout the study. Two hundred, 3-day old adults of F1 generation Anopheles funestus collected by aspiration or F0 reared from An. arabiensis larvae or An. arabiensis (Dongola strain) were released in each semi-field structure at dusk and recaptured the following morning. A single volunteer slept in each hut under an untreated bednet each night of the study. Recaptured mosquitoes were counted and recorded by location, either indoor or outdoor of each hut in the different semi-field structures.

Results

Based on modelled estimates, significantly fewer, 10% An. arabiensis from Ahero, 11% An. arabiensis Dongola strain and 10% An. funestus from Siaya were observed inside modified huts compared to unmodified ones. Treating of eave screen material with Actellic® 300CS significantly reduced indoor numbers of An. arabiensis from Ahero, to nearly 0%, and An. arabiensis Dongola strain, to 3%, compared to huts with untreated eave screens, while eliminating An. funestus indoors. These modifications cost US$180 /structure and have been observed to last more than 15 years in a different location.

Conclusions

Eave, door and window screening are effective ways of reducing mosquito entry into houses. Additionally, treatment of eave screen material with an effective insecticide further reduces the Anopheles population in and around the screened huts under semi-field conditions and could greatly complement existing vector control efforts.

Association between Livestock Ownership and Malaria Incidence in South-Central Ethiopia: A Cohort Study

Zooprophylaxis is one of the possible environmental vector control strategies for malaria prevention. However, its effect on reducing malaria transmission has been questionable, requiring a detailed understanding of contextual factors. This study aims to evaluate the effect of keeping livestock on malaria incidence in south-central Ethiopia. A cohort of 34,548 people in a total of 6,071 households was followed for 121 weeks from October 2014 to January 2017. Baseline data were collected, including livestock ownership. Weekly home visits were done to actively search for malaria cases, and passive case detection was also carried out. Malaria was diagnosed with rapid diagnostic tests. Log binomial and parametric regression survival-time models were used to estimate effect measures. A total of 27,471 residents had complete follow-ups, and the majority (87.5%) lived in households owning livestock, including cattle, sheep, goats, and chickens. The overall incidence risk of malaria was 3.7%, and there was a 24% reduction in the risk of malaria among livestock owners. The total cohort contributed to 71,861.62 person-years of observation. The incidence rate of malaria was 14.7 cases per 1,000 person-years. There was a 17% reduction in the rate of malaria among livestock owners. Meanwhile, the protective effect of livestock ownership increased as the number of livestock or the livestock-to-human ratio increased. In conclusion, livestock owners had less malaria. In a setup where domestication of livestock is a common practice and the predominant malaria vector tends to feed more on livestock than humans, zooprophylaxis remains a promising strategy for malaria prevention.

The spatial signature of Plasmodium vivax and Plasmodium falciparum infections: quantifying the clustering of infections in cross-sectional surveys and cohort studies

BACKGROUND

Over the last decades, enormous successes have been achieved in reducing malaria burden globally. In Latin America, South East Asia, and the Western Pacific, many countries now pursue the goal of malaria elimination by 2030. It is widely acknowledged that Plasmodium spp. infections cluster spatially so that interventions need to be spatially informed, e.g. spatially targeted reactive case detection strategies. Here, the spatial signature method is introduced as a tool to quantify the distance around an index infection within which other infections significantly cluster.

METHODS

Data were considered from cross-sectional surveys from Brazil, Thailand, Cambodia, and Solomon Islands, conducted between 2012 and 2018. Household locations were recorded by GPS and finger-prick blood samples from participants were tested for Plasmodium infection by PCR. Cohort studies from Brazil and Thailand with monthly sampling over a year from 2013 until 2014 were also included. The prevalence of PCR-confirmed infections was calculated at increasing distance around index infections (and growing time intervals in the cohort studies). Statistical significance was defined as prevalence outside of a 95%-quantile interval of a bootstrap null distribution after random re-allocation of locations of infections.

RESULTS

Prevalence of Plasmodium vivax and Plasmodium falciparum infections was elevated in close proximity around index infections and decreased with distance in most study sites, e.g. from 21.3% at 0 km to the global study prevalence of 6.4% for P. vivax in the Cambodian survey. In the cohort studies, the clustering decreased with longer time windows. The distance from index infections to a 50% reduction of prevalence ranged from 25 m to 3175 m, tending to shorter distances at lower global study prevalence.

CONCLUSIONS

The spatial signatures of P. vivax and P. falciparum infections demonstrate spatial clustering across a diverse set of study sites, quantifying the distance within which the clustering occurs. The method offers a novel tool in malaria epidemiology, potentially informing reactive intervention strategies regarding radius choices of operations around detected infections and thus strengthening malaria elimination endeavours.

Screening eaves of houses reduces indoor mosquito density in rural, western Kenya

BACKGROUND

Despite the scale-up of insecticide-treated nets and indoor residual spraying, the bulk of malaria transmission in western Kenya still occurs indoors, late at night. House improvement is a potential long-term solution to further reduce malaria transmission in the region.

METHODS

The impact of eave screening on mosquito densities was evaluated in two rural villages in western Kenya. One-hundred-and-twenty pairs of structurally similar, neighbouring houses were used in the study. In each pair, one house was randomly selected to receive eave screening at the beginning of the study while the other remained unscreened until the end of the sampling period. Mosquito sampling was performed monthly by motorized aspiration method for 4 months. The collected mosquitoes were analysed for species identification.

RESULTS

Compared to unscreened houses, significantly fewer female Anopheles funestus (RR = 0.40, 95% CI 0.29-0.55), Anopheles gambiae Complex (RR = 0.46, 95% CI 0.34-0.62) and Culex species (RR = 0.53, 95% CI 0.45-0.61) were collected in screened houses. No significant differences in the densities of the mosquitoes were detected in outdoor collections. Significantly fewer Anopheles funestus were collected indoors from houses with painted walls (RR = 0.05, 95% CI 0.01-0.38) while cooking in the house was associated with significantly lower numbers of Anopheles gambiae Complex indoors (RR = 0.60, 95% CI 0.45-0.79). Nearly all house owners (99.6%) wanted their houses permanently screened, including 97.7% that indicated a willingness to use their own resources. However, 99.2% required training on house screening. The cost of screening a single house was estimated at KES6,162.38 (US$61.62).

CONCLUSION

Simple house modification by eave screening has the potential to reduce the indoor occurrence of both Anopheles and Culex mosquito species. Community acceptance was very high although education and mobilization may be needed for community uptake of house modification for vector control. Intersectoral collaboration and favourable government policies on housing are important links towards the adoption of house improvements for malaria control.

Differences in diagnosis, management, and outcomes of acute febrile illness by health facility level in southern Ethiopia

We assessed the diagnosis, management and outcomes of acute febrile illness in a cohort of febrile children aged under 5 years presenting at one urban and two rural health centres and one tertiary hospital between 11 August 2019 and 01 November 2019. Pneumonia was diagnosed in 104 (30.8%) of 338 children at health centres and 128 (65.0%) of 197 at the hospital (p < 0.001). Malaria was detected in 33 (24.3%) of 136 children at the urban health centre, and in 55 (55.6%) of 99 and 7 (7.4%) of 95 children at the rural health centres compared to 11 (11.6%) of 95 at the hospital. Antibacterials were prescribed to 20 (11.5%) of 174 children without guidelines-specified indications (overprescribing) at health centres and in 7 (33.3%) of 21 children at the hospital (p = 0.013). Antimalarials were overprescribed to 13 (7.0%) of 185 children with negative malaria microscopy at the hospital. The fever resolved by day 7 in 326 (99.7%) of 327 children at health centres compared to 177 (93.2%) of 190 at the hospital (p < 0.001). These results suggest that additional guidance to health workers is needed to optimise the use of antimicrobials across all levels of health facilities.

A meta-epidemiological assessment of transparency indicators of infectious disease models

Mathematical models have become very influential, especially during the COVID-19 pandemic. Data and code sharing are indispensable for reproducing them, protocol registration may be useful sometimes, and declarations of conflicts of interest (COIs) and of funding are quintessential for transparency. Here, we evaluated these features in publications of infectious disease-related models and assessed whether there were differences before and during the COVID-19 pandemic and for COVID-19 models versus models for other diseases. We analysed all PubMed Central open access publications of infectious disease models published in 2019 and 2021 using previously validated text mining algorithms of transparency indicators. We evaluated 1338 articles: 216 from 2019 and 1122 from 2021 (of which 818 were on COVID-19); almost a six-fold increase in publications within the field. 511 (39.2%) were compartmental models, 337 (25.2%) were time series, 279 (20.9%) were spatiotemporal, 186 (13.9%) were agent-based and 25 (1.9%) contained multiple model types. 288 (21.5%) articles shared code, 332 (24.8%) shared data, 6 (0.4%) were registered, and 1197 (89.5%) and 1109 (82.9%) contained COI and funding statements, respectively. There was no major changes in transparency indicators between 2019 and 2021. COVID-19 articles were less likely to have funding statements and more likely to share code. Further validation was performed by manual assessment of 10% of the articles identified by text mining as fulfilling transparency indicators and of 10% of the articles lacking them. Correcting estimates for validation performance, 26.0% of papers shared code and 41.1% shared data. On manual assessment, 5/6 articles identified as registered had indeed been registered. Of articles containing COI and funding statements, 95.8% disclosed no conflict and 11.7% reported no funding. Transparency in infectious disease modelling is relatively low, especially for data and code sharing. This is concerning, considering the nature of this research and the heightened influence it has acquired.

Spatiotemporal variation of malaria incidence in parasite clearance interventions and non-intervention areas in the Amhara Regional State, Ethiopia

Background

In Ethiopia, malaria remains a major public health problem. To eliminate malaria, parasite clearance interventions were implemented in six kebeles (the lowest administrative unit) in the Amhara region. Understanding the spatiotemporal distribution of malaria is essential for targeting appropriate parasite clearance interventions to achieve the elimination goal. However, little is known about the spatiotemporal distribution of malaria incidence in the intervention and non-intervention areas. This study aimed to investigate the spatiotemporal distribution of community-based malaria in the intervention and non-intervention kebeles between 2013 and 2018 in the Amhara Regional State, Ethiopia.

Methods

Malaria data from 212 kebeles in eight districts were downloaded from the District Health Information System2 (DHIS2) database. We used Autoregressive integrated moving average (ARIMA) model to investigate seasonal variations; Anselin Local Moran’s I statistical analysis to detect hotspot and cold spot clusters of malaria cases; and a discrete Poisson model using Kulldorff scan statistics to identify statistically significant clusters of malaria cases.

Results

The result showed that the reduction in the trend of malaria incidence was higher in the intervention areas compared to the non-intervention areas during the study period with a slope of -0.044 (-0.064, -0.023) and -0.038 (-0.051, -0.024), respectively. However, the difference was not statistically significant. The Global Moran’s I statistics detected the presence of malaria clusters (z-score = 12.05; p<0.001); the Anselin Local Moran’s I statistics identified hotspot malaria clusters at 21 locations in Gendawuha and Metema districts. A statistically significant spatial, temporal, and space-time cluster of malaria cases were detected. Most likely type of spatial clusters of malaria cases (LLR = 195501.5; p <0.001) were detected in all kebeles of Gendawuha and Metema districts. The temporal scan statistic identified three peak periods between September 2013 and November 2015 (LLR = 8727.5; p<0.001). Statistically significant most-likely type of space-time clusters of malaria cases (LLR = 97494.3; p<0.001) were detected at 22 locations from June 2014 to November 2016 in Metema district.

Conclusion

There was a significant decline in malaria incidence in the intervention areas. There were statistically significant spatiotemporal variations of malaria in the study areas. Applying appropriate parasite clearance interventions is highly recommended for the better achievement of the elimination goal. A more rigorous evaluation of the impact of parasite clearance interventions is recommended.

Epidemic malaria dynamics in Ethiopia: the role of self-limiting, poverty, HIV, climate change and human population growth

Background

During the last two decades, researchers have suggested that the changes of malaria cases in African highlands were driven by climate change. Recently, a study claimed that the malaria cases (Plasmodium falciparum) in Oromia (Ethiopia) were related to minimum temperature. Critics highlighted that other variables could be involved in the dynamics of the malaria. The literature mentions that beyond climate change, trends in malaria cases could be involved with HIV, human population size, poverty, investments in health control programmes, among others.

Methods

Population ecologists have developed a simple framework, which helps to explore the contributions of endogenous (density-dependent) and exogenous processes on population dynamics. Both processes may operate to determine the dynamic behaviour of a particular population through time. Briefly, density-dependent (endogenous process) occurs when the per capita population growth rate (R) is determined by the previous population size. An exogenous process occurs when some variable affects another but is not affected by the changes it causes. This study explores the dynamics of malaria cases (Plasmodium falciparum and Plasmodium vivax) in Oromia region in Ethiopia and explores the interaction between minimum temperature, HIV, poverty, human population size and social instability.

Results

The results support that malaria dynamics showed signs of a negative endogenous process between R and malaria infectious class, and a weak evidence to support the climate change hypothesis.

Conclusion

Poverty, HIV, population size could interact to force malaria models parameters explaining the dynamics malaria observed at Ethiopia from 1985 to 2007.

Clustering of malaria in households in the Greater Mekong Subregion: operational implications for reactive case detection

Background

Malaria reactive case detection is the testing and, if positive, treatment of close contacts of index cases. It is included in national malaria control programmes of countries in the Greater Mekong Subregion to accelerate malaria elimination. Yet the value of reactive case detection in the control and elimination of malaria remains controversial because of the low yield, limited evidence for impact, and high demands on resources.

Methods

Data from the epidemiological assessments of large mass drug administration (MDA) studies in Myanmar, Vietnam, Cambodia and Laos were analysed to explore malaria infection clustering in households. The proportion of malaria positive cases among contacts screened in a hypothetical reactive case detection programme was then determined. The parasite density thresholds for rapid diagnostic test (RDT) detection was assumed to be > 50/µL (50,000/mL), for dried-blood-spot (DBS) based PCR > 5/µL (5000/mL), and for ultrasensitive PCR (uPCR) with a validated limit of detection at 0.0022/µL (22/mL).

Results

At baseline, before MDA, 1223 Plasmodium infections were detected by uPCR in 693 households. There was clustering of Plasmodium infections. In 637 households with asymptomatic infections 44% (278/637) had more than one member with Plasmodium infections. In the 132 households with symptomatic infections, 65% (86/132) had more than one member with Plasmodium infections. At baseline 4% of households had more than one Plasmodium falciparum infection, but three months after MDA no household had more than one P. falciparum infected member. Reactive case detection using DBS PCR would have detected ten additional cases in six households, and an RDT screen would have detected five additional cases in three households among the 169 households with at least one RDT positive case. This translates to 19 and 9 additional cases identified per 1000 people screened, respectively. Overall, assuming all febrile RDT positive patients would seek treatment and provoke reactive case detection using RDTs, then 1047 of 1052 (99.5%) Plasmodium infections in these communities would have remained undetected.

Conclusion

Reactive case detection in the Greater Mekong subregion is predicted to have a negligible impact on the malaria burden, but it has substantial costs in terms of human and financial resources.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-021-03879-9.

Spatial and spatio-temporal methods for mapping malaria risk: a systematic review

Background

Approaches in malaria risk mapping continue to advance in scope with the advent of geostatistical techniques spanning both the spatial and temporal domains. A substantive review of the merits of the methods and covariates used to map malaria risk has not been undertaken. Therefore, this review aimed to systematically retrieve, summarise methods and examine covariates that have been used for mapping malaria risk in sub-Saharan Africa (SSA).

Methods

A systematic search of malaria risk mapping studies was conducted using PubMed, EBSCOhost, Web of Science and Scopus databases. The search was restricted to refereed studies published in English from January 1968 to April 2020. To ensure completeness, a manual search through the reference lists of selected studies was also undertaken. Two independent reviewers completed each of the review phases namely: identification of relevant studies based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, data extraction and methodological quality assessment using a validated scoring criterion.

Results

One hundred and seven studies met the inclusion criteria. The median quality score across studies was 12/16 (range: 7–16). Approximately half (44%) of the studies employed variable selection techniques prior to mapping with rainfall and temperature selected in over 50% of the studies. Malaria incidence (47%) and prevalence (35%) were the most commonly mapped outcomes, with Bayesian geostatistical models often (31%) the preferred approach to risk mapping. Additionally, 29% of the studies employed various spatial clustering methods to explore the geographical variation of malaria patterns, with Kulldorf scan statistic being the most common. Model validation was specified in 53 (50%) studies, with partitioning data into training and validation sets being the common approach.

Conclusions

Our review highlights the methodological diversity prominent in malaria risk mapping across SSA. To ensure reproducibility and quality science, best practices and transparent approaches should be adopted when selecting the statistical framework and covariates for malaria risk mapping. Findings underscore the need to periodically assess methods and covariates used in malaria risk mapping; to accommodate changes in data availability, data quality and innovation in statistical methodology.

Older children are at increased risk of Plasmodium vivax in south-central Ethiopia: a cohort study

BACKGROUND

Better understanding of the distribution of Plasmodium vivax and its risk factors could be used to prevent and control malaria infection. Therefore, the aim of this study was to characterize the distribution and risk factors of P. vivax, and to compare them with Plasmodium falciparum occurrence in south-central Ethiopia.

METHODS

A cohort of 34,548 individuals were followed for 121 weeks between 2014 and 2016 as part of larger cluster randomized controlled trial to evaluate the effect of long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) on malaria prevention in Ethiopia. Weekly home visit (active search) and patient self- report to health post (passive search) between the weekly home visits were used to register malaria cases. A blood sample was collected by finger prick and malaria was diagnosed using rapid diagnostic test (RDT). Generalized estimating equation (GEE) Poisson model that accounts for repeated measure of malaria episodes was applied to assess the risk factors of P. vivax episode.

RESULTS

The overall incidence rate of P. vivax was 7.4 episodes per 1000 person-years of observation. The study showed households closer to the lake Zeway and Bulbula river (potential mosquito breeding sites) were more at risk of P. vivax infection (incidence rate ratio (IRR): 1.33; 95% CI = 1.23-1.45). Furthermore, the age group under 5 years (IRR: 1.40, 95% CI = 1.10-1.79), the age group 5-14 years (IRR: 1.27, 95% CI = 1.03-1.57), households with less educated household head (IRR: 1.63, 95% CI = 1.10-2.44) and house roof made of thatch/leaf (IRR: 1.35, 95% CI = 1.11-1.65) were at higher risk for P. vivax. Similar explanatory variables such as distance from the breeding sites, age group (under 5 years but not 5-14 years old), educational status and type of housing were also found to be the predictors of P. falciparum incidence.

CONCLUSION

Households living closer to a mosquito breeding site, age group under 15 years, less educated household heads and thatch/leaf roof housing were the risk factor for P. vivax. The result of this study can be used for tailored interventions for malaria control and prevention by prioritizing those living close to potential mosquito breeding site, enhancing bed net use of children less than 15 years of age, and improving housing.

Spatial and Temporal Patterns of Plasmodium knowlesi Malaria in Sarawak from 2008 to 2017

Zoonotic knowlesi malaria has replaced human malaria as the most prevalent malaria disease in Malaysia. The persistence of knowlesi malaria in high-risk transmission areas or hotspots can be discouraging to existing malaria elimination efforts. In this study, retrospective data of laboratory-confirmed knowlesi malaria cases were obtained from the Sarawak Health Department to investigate the spatiotemporal patterns and clustering of knowlesi malaria in the state of Sarawak from 2008 to 2017. Purely spatial, purely temporal, and spatiotemporal analyses were performed using SaTScan software to define clustering of knowlesi malaria incidence. Purely spatial and spatiotemporal analyses indicated most likely clusters of knowlesi malaria in the northern region of Sarawak, along the Sarawak-Kalimantan border, and the inner central region of Sarawak between 2008 and 2017. Temporal cluster was detected between September 2016 and December 2017. This study provides evidence of the existence of statistically significant Plasmodium knowlesi malaria clusters in Sarawak, Malaysia. The analysis approach applied in this study showed potential in establishing surveillance and risk management system for knowlesi malaria control as Malaysia approaches human malaria elimination.

Spatial and Temporal Analysis of Plasmodium knowlesi Infection in Peninsular Malaysia, 2011 to 2018

The life-threatening zoonotic malaria cases caused by Plasmodium knowlesi in Malaysia has recently been reported to be the highest among all malaria cases; however, previous studies have mainly focused on the transmission of P. knowlesi in Malaysian Borneo (East Malaysia). This study aimed to describe the transmission patterns of P. knowlesi infection in Peninsular Malaysia (West Malaysia). The spatial distribution of P. knowlesi was mapped across Peninsular Malaysia using Geographic Information System techniques. Local indicators of spatial associations were used to evaluate spatial patterns of P. knowlesi incidence. Seasonal autoregressive integrated moving average models were utilized to analyze the monthly incidence of knowlesi malaria in the hotspot region from 2012 to 2017 and to forecast subsequent incidence in 2018. Spatial analysis revealed that hotspots were clustered in the central-northern region of Peninsular Malaysia. Time series analysis revealed the strong seasonality of transmission from January to March. This study provides fundamental information on the spatial distribution and temporal dynamic of P. knowlesi in Peninsular Malaysia from 2011 to 2018. Current control policy should consider different strategies to prevent the transmission of both human and zoonotic malaria, particularly in the hotspot region, to ensure a successful elimination of malaria in the future.