Spatiotemporal patterns of malaria at cross-boundaries area in Menoreh Hills, Java, Indonesia

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.

Space-time cluster detection techniques for infectious diseases: A systematic review

BACKGROUND

Public health organizations have increasingly harnessed geospatial technologies for disease surveillance, health services allocation, and targeting place-based health promotion initiatives.

METHODS

We conducted a systematic review around the theme of space-time clustering detection techniques for infectious diseases using PubMed, Web of Science, and Scopus. Two reviewers independently determined inclusion and exclusion.

RESULTS

Of 2,887 articles identified, 354 studies met inclusion criteria, the majority of which were application papers. Studies of airborne diseases were dominant, followed by vector-borne diseases. Most research used aggregated data instead of point data, and a significant proportion of articles used a repetition of a spatial clustering method, instead of using a "true" space-time detection approach, potentially leading to the detection of false positives. Noticeably, most articles did not make their data available, limiting replicability.

CONCLUSION

This review underlines recent trends in the application of space-time clustering methods to the field of infectious disease, with a rapid increase during the COVID-19 pandemic.

Migration Surveillance as a Maintenance Effort of Malaria Elimination Status (Study in Banyumas Regency, Central Java, Indonesia, 2021)

Background: Banyumas Regency is a malaria-receptive area with the occurrence of imported cases, particularly in sub-districts with the potential for transmission and even extraordinary events. To eliminate malaria in the regency, Migration surveillance is needed. Therefore, this study aims to evaluate implementing a malaria migration surveillance system to maintain its elimination status in Banyumas Regency in 2021. Method: This qualitative case study was conducted in Banyumas Regency with a total of 9 informants consisting of 2 people from the Health Office, 4 from the Community Health Center, 2 from the Health Laboratory, and 1 village head. Data was collected through Forum Group Discussions, in-depth interviews, and secondary data through document review. This study also adopted content analysis with a thematic network approach. Result: There are several limitations to implementing malaria migration surveillance, namely the lack of human resources, ineffective implementation of village regulations, and the lack of public awareness in reporting symptoms of malaria. Therefore, comprehensive training, policies socialization, improved partnerships, and application-based village reporting are required to maintain the elimination of migration surveillance.

Clusters of malaria cases at sub-district level in endemic area in Java Island, Indonesia

Malaria remains one of the essential public health problems in Indonesia. The year 2015 was originally set as the elimination target in Java Island, but there are still several regencies on Java reporting malaria cases. Spatial technology helps determine local variations in malaria transmission, control risk areas and assess the outcome of interventions. Information on distribution patterns of malaria at the sub-district level, presented as spatial, temporal, and spatiotemporal data, is vital in planning control interventions. Information on malaria transmission at the sub-district level in three regencies in Java (Banyumas, Kebumen, and Purbalingga) was collected from the Agency for Regional Development (Bappeda), the Population and Civil Registration Agency (Disdukcapil) and Statistics Indonesia (BPS). Global spatial autocorrelation and space-time clustering was investigated together with purely spatial and purely temporal analyses using geographical information systems (GIS) by ArcGis 10.2 and SaTScan 8.0 to detect areas at high risk of malaria. Our results show that malaria was spatially clustered in the study area in central Java, in particular in the Banyumas and Purbalingga regencies. The temporal analysis revealed that malaria clusters predominantly appeared in the period January-April. The results of the spatiotemporal analysis showed that there was one most likely malaria cluster and three secondary clusters in southern central Java. The most likely cluster was located in Purbalingga Regency covering one sub-district and remaining from the beginning of 2016 to the end of 2018. The approach used can assist the setting of resource priorities to control and eliminate malaria.

Risk Factors Analysis of Malaria Transmission at Cross-Boundaries Area in Menoreh Hills, Java, Indonesia

Background:

Risk factors of Malaria transmission at cross-boundaries area is important to be identified. This study aimed to identify the risk factors of Malaria transmission at cross-boundaries area in Menoreh Hills, Java, Indonesia.

Methods:

The design of the study was an observational study with a case-control design. Data on malaria cases and controls were obtained from the Primary Health Care in Menoreh. All malaria positive patients with clinical and laboratory examinations recorded in health services during 1 Jan 2015–31 Dec 2015. Overall, 138 cases and 138 controls were included. Several variables were collected such as altitude, night out behavior, the use of mosquito nets, nighttime bed, travel history, mosquito bite prevention activities, cattle ownership, distance to mosquito breeding site, etc. Data were obtained by structured questionnaires and observation. Data were analyzed by univariate, bivariate and multivariate

Results:

The altitude of house >500 m above sea level proved to be influential as a risk factor for Malaria (OR 3.62, 95% CI 1.61–8.16, P=0.002). Several variables were identified as a risk factor of Malaria such as the wall of the house from bamboo/wood, no insecticide and distance of house <100 m from mosquito breeding site.

Conclusion:

An awareness for the local health sector particularly to provide a recommendation for house construction to protect a community from Malaria transmission.

Spatial analysis of malaria in Kotabaru, South Kalimantan, Indonesia: an evaluation to guide elimination strategies

BACKGROUND

Malaria remains a significant public health concern in Indonesia. Knowledge about spatial patterns of the residual malaria hotspots is critical to help design elimination strategies in Kotabaru district, South Kalimantan, Indonesia.

METHODS

Laboratory-confirmed malaria cases from 2012 to 2016 were analysed to examine the trend in malaria cases. Decomposition analysis was performed to assess seasonality. Annual spatial clustering of the incidence and hotspots were identified by Moran's I and the local indicator for spatial association, respectively.

RESULTS

The annual parasite incidence of malaria was significantly reduced by 87% from 2012 to 2016. Plasmodium vivax infections were significantly much more prevalent over time, followed by Plasmodium falciparum infections (p<0.001). The monthly seasonality of P. vivax and P. falciparum was distinct. High incidence was spatially clustered identified in the north, west and parts of south Kotabaru. Two persistent and four re-emerging high-risk clusters were identified during the period. Despite the significant reduction in the incidence of malaria, the residual high-risk villages remained clustered in the northern part of Kotabaru.

CONCLUSIONS

A spatially explicit decision support system is needed to support surveillance and control programs in the identified high-risk areas to succeed in the elimination goal of 2030.

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.

Using global positioning system technology and Google My Maps in follow-up studies-An experience from influenza surveillance study, Chennai, India

A multi-centric influenza surveillance conducted among 1500 elderly participants in Chennai, India, required weekly visits to the participants regularly for three years. Difficulties were faced in locating and navigating to households of the participants due to vast study area, adverse weather conditions and staff attrition, which affected data quality. To overcome these difficulties, we devised a new way of using the 'Global Position System' (GPS) and 'Google My Maps'. GPS coordinates of all participants' households were collected and merged with their demographic data using 'Microsoft excel'. Dataset was uploaded to 'Google My Maps' in appropriate layers. This map was used to locate and navigate to households of the participants and the average working hours in the field reduced by18% even in difficult circumstances. The average number of supervisory visits increased by 150%. This method will greatly facilitate the data collection in cohort based research studies.

Using health facility-based serological surveillance to predict receptive areas at risk of malaria outbreaks in elimination areas

BACKGROUND

In order to improve malaria burden estimates in low transmission settings, more sensitive tools and efficient sampling strategies are required. This study evaluated the use of serological measures from repeated health facility-based cross-sectional surveys to investigate Plasmodium falciparum and Plasmodium vivax transmission dynamics in an area nearing elimination in Indonesia.

METHODS

Quarterly surveys were conducted in eight public health facilities in Kulon Progo District, Indonesia, from May 2017 to April 2018. Demographic data were collected from all clinic patients and their companions, with household coordinates collected using participatory mapping methods. In addition to standard microscopy tests, bead-based serological assays were performed on finger-prick bloodspot samples from 9453 people. Seroconversion rates (SCR, i.e. the proportion of people in the population who are expected to seroconvert per year) were estimated by fitting a simple reversible catalytic model to seroprevalence data. Mixed effects logistic regression was used to examine factors associated with malaria exposure, and spatial analysis was performed to identify areas with clustering of high antibody responses.

RESULTS

Parasite prevalence by microscopy was extremely low (0.06% (95% confidence interval 0.03-0.14, n = 6) and 0 for P. vivax and P. falciparum, respectively). However, spatial analysis of P. vivax antibody responses identified high-risk areas that were subsequently the site of a P. vivax outbreak in August 2017 (62 cases detected through passive and reactive detection systems). These areas overlapped with P. falciparum high-risk areas and were detected in each survey. General low transmission was confirmed by the SCR estimated from a pool of the four surveys in people aged 15 years old and under (0.020 (95% confidence interval 0.017-0.024) and 0.005 (95% confidence interval 0.003-0.008) for P. vivax and P. falciparum, respectively). The SCR estimates in those over 15 years old were 0.066 (95% confidence interval 0.041-0.105) and 0.032 (95% confidence interval 0.015-0.069) for P. vivax and P. falciparum, respectively.

CONCLUSIONS

These findings demonstrate the potential use of health facility-based serological surveillance to better identify and target areas still receptive to malaria in an elimination setting. Further implementation research is needed to enable integration of these methods with existing surveillance systems.