Spatial temporal distribution of COVID-19 risk during the early phase of the pandemic in Malawi

Ngwira, Alfred; Kumwenda, Felix; Munthali, Eddons C.S.; Nkolokosa, Duncan

doi:10.7717/peerj.11003

Cited by 11 publications

(20 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The socioeconomic heterogeneity between districts occupied within regions in Malaysia may have influenced the uneven chaotic spreads, as marked spatial heterogeneity of incidence cases were observed between the East Coast region, East Malaysia (particularly the state of Sarawak) and the Central region of Malaysia, among which the latter represents a highly industrialized, economic and financial epicenter of the country. This finding was consistent with previous studies from Brazil [ 38 ], India [ 43 ], China [ 44 ], Malawi [ 22 ] and England [ 19 ]. Plausible explanations for such consistencies can be attributed to selective migration of people, facilitating large territorial flows from neighboring regions or states to the Central region of the country to capture potential commercial or labor markets that could have substantially cultivated dense populations in those areas, causing greater human mobility and interactions.…”

Section: Discussionsupporting

confidence: 94%

“…Understanding the aspects of transmissibility based on place would be crucial to execute disease control and harm reduction strategies. While the spatial dispersion of COVID-19 has observed specific flows within regions or territories from different countries [ 17 , 18 , 19 , 20 , 21 , 22 , 23 ], their temporal relationships vary, in particular to those related to social determinants of health as a medium of spread for COVID-19 [ 18 , 22 , 24 ]. Malaysia was nearly successful in containing the outbreak in the previous two waves [ 25 , 26 ], but the current third wave of the pandemic, likely to be caused by spillover effects of a regional state election in late 2020 [ 27 ], seemed difficult to contain.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Spatial Dynamics and Multiscale Regression Modelling of Population Level Indicators for COVID-19 Spread in Malaysia

Ganasegeran

Jamil

Appannan

et al. 2022

IJERPH

View full text Add to dashboard Cite

As COVID-19 dispersion occurs at different levels of gradients across geographies, the application of spatiotemporal science via computational methods can provide valuable insights to direct available resources and targeted interventions for transmission control. This ecological-correlation study evaluates the spatial dispersion of COVID-19 and its temporal relationships with crucial demographic and socioeconomic determinants in Malaysia, utilizing secondary data sources from public domains. By aggregating 51,476 real-time active COVID-19 case-data between 22 January 2021 and 4 February 2021 to district-level administrative units, the incidence, global and local Moran indexes were calculated. Spatial autoregressive models (SAR) complemented with geographical weighted regression (GWR) analyses were executed to determine potential demographic and socioeconomic indicators for COVID-19 spread in Malaysia. Highest active case counts were based in the Central, Southern and parts of East Malaysia regions of Malaysia. Countrywide global Moran index was 0.431 (p = 0.001), indicated a positive spatial autocorrelation of high standards within districts. The local Moran index identified spatial clusters of the main high–high patterns in the Central and Southern regions, and the main low–low clusters in the East Coast and East Malaysia regions. The GWR model, the best fit model, affirmed that COVID-19 spread in Malaysia was likely to be caused by population density (β coefficient weights = 0.269), followed by average household income per capita (β coefficient weights = 0.254) and GINI coefficient (β coefficient weights = 0.207). The current study concluded that the spread of COVID-19 was concentrated mostly in the Central and Southern regions of Malaysia. Population’s average household income per capita, GINI coefficient and population density were important indicators likely to cause the spread amongst communities.

show abstract

Section: Discussionsupporting

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Spatial Dynamics and Multiscale Regression Modelling of Population Level Indicators for COVID-19 Spread in Malaysia

Ganasegeran

Jamil

Appannan

et al. 2022

IJERPH

View full text Add to dashboard Cite

show abstract

“…This differs to the second wave, which was not only more rapid in its growth but also in its geographic spread, as shown by the high seroprevalence even in the rural areas. This is consistent with national surveillance reports showing that confirmed COVID-19 cases in the first wave were primarily from the three major cities, Blantyre, Lilongwe and Mzuzu, but in the second wave there was an increase in reported cases in rural areas 39,40 . Also noteworthy is the earlier seroprevalence peak in Blantyre and Lilongwe, compared to the northern city of Mzuzu.…”

Section: Discussionsupporting

confidence: 90%

Dynamics of SARS-CoV-2 exposure in Malawian blood donors: a retrospective seroprevalence analysis between January 2020 and February 2021

Mandolo

Msefula

Henrion

et al. 2021

Preprint

View full text Add to dashboard Cite

BackgroundAs at end of July 2021, the COVID-19 pandemic has been less severe in sub-Saharan Africa than elsewhere. In Malawi, there have been two subsequent epidemic waves. We therefore aimed to describe the dynamics of SARS-CoV-2 exposure in Malawi.MethodsWe measured the seroprevalence of anti-SARS-CoV-2 antibodies among randomly selected blood donor sera in Malawi from January 2020 to February 2021. In a subset, we also assesed in vitro neutralisation against the original variant (D614G WT) and the Beta variant.FindingsA total of 3586 samples were selected from the blood donor database, of which 2685 (74.9%) were male and 3132 (87.3%) were aged 20-49 years. Of the total, 469 (13.1%) were seropositive. Seropositivity was highest in October 2020 (15.7%) and February 2021 (49.7%) reflecting the two epidemic waves. Unlike the first wave, both urban and rural areas had high seropositivity by February 2021, Balaka (rural, 37.5%), Blantyre (urban, 54.8%), Lilongwe (urban, 54.5%) and Mzuzu (urban, 57.5%). First wave sera showed potent in vitro neutralisation activity against the original variant (78%[7/9]) but not the Beta variant (22% [2/9]). Second wave sera potently neutralised the Beta variant (73% [8/11]).InterpretationThe findings confirm extensive SARS-CoV-2 exposure in Malawi over two epidemic waves with likely poor cross-protection to reinfection from the first on the second wave. Since prior exposure augments COVID-19 vaccine immunity, prioritising administration of the first dose in high SARS-CoV-2 exposure settings could maximise the benefit of the limited available vaccines in Malawi and the region.Research in contextEvidence before this studyWe searched PubMed on August 16, 2021, with no language restrictions, for titles and abstracts published between Jan 1, 2020, and August 16, 2021, using the search terms: “SARS-CoV-2 seroprevalence in Africa”[Title/Abstract]) OR “SARS-CoV-2 seroprevalence in blood donors” [Title/Abstract] OR “SARS-CoV-2 seroprevalence in Malawi”, and found 15 records. There are limited SARS-CoV-2 seroprevalence studies in sub Saharan Africa, however the few that are available report high seroprevalence than can be deduced from the respective national reported COVID-19 cases and deaths. Only two published SARS-CoV-2 serosurveys were done on blood donors, from Kenya and Madagascar. Blood donor serosurveys have been recommended by the WHO as an important tool for assessing the spread of SARS-CoV-2 and estimating the burden of COVID-19 pandemic.Added value of this studyUnlike previous SARS-CoV-2 blood donor serosurveys in African populations that were conducted for a maximum period of 9 months, our study covers a full year from January 2020 to February 2021, capturing potential introduction of SARS-CoV-2 into Malawi as well as the two epidemic waves. This study provides evidence against the speculation that SARS-CoV-2 had been circulating more widely in sub-Saharan Africa before the first detected cases. It also provides supporting evidence suggesting that the Beta variant was the likely driver of the second wave that resulted in high SARS-CoV-2 seropositivity in January to February 2021 in Malawi.Implications of all the available evidenceOur results show extensive community transmission of SARS-CoV-2 in Malawi as reflected in the blood donors serosurvey, with almost half the sample population being seropositive for anti-SARS-CoV-2 antibodies by February 2021. This has implications for COVID-19 vaccination policy in sub-Saharan Africa (SSA), where there are limited available vaccine doses. Considering that prior exposure to SARS-CoV-2 augments COVID-19 vaccine immunity, strategies to maximise administration of the first vaccine dose, while waiting for more vaccines to become available, could maximise the benefits of the limited available vaccines in high SARS-CoV-2 exposure settings in SSA such as Malawi.

show abstract

“…Until now, studies evaluating the epidemiological and spatial spread of COVID-19 in Africa have been limited. Understanding the spread of the pandemic is critical for predicting local outbreaks and developing public health policies during the early stages of COVID-19 ( 10 , 11 ).…”

Section: Introductionmentioning

confidence: 99%

The Epidemiological and Spatiotemporal Characteristics of the 2019 Novel Coronavirus Disease (COVID-19) in Libya

Daw

El-Bouzedi

Ahmed

2021

Front. Public Health

View full text Add to dashboard Cite

COVID-19 is a global pandemic that has affected all aspects of life. Understanding its geographical and epidemiological characteristics has become particularly important in controlling the spread of the pandemic. Such studies are lacking in North African countries, particularly in Libya, which has the second largest area of any country in Africa and the longest coast facing Europe. The objectives of this study are to determine the epidemiological parameters and spatiotemporal patterns of COVID-19 and outline strategies for containing the spread and consequences of the pandemic. This comprehensive study included all the confirmed cases of COVID-19 since its emergence in Libya on March 24, 2020 until July 31, 2020. The epidemiological characteristics of COVID-19 were analyzed and the spatial dynamic trends were explored. Regional counts of weekly reported cases were used to characterize the spatial dynamics of COVID-19. A total of 3,695 confirmed cases of COVID-19 were recorded: 2,515 men (68.1%) and 1,180 women (31.9%), with a male-to-female ratio of 2.1:1. Ages ranged between 2 and 78 years. Older patients infected with COVID-19 were at a risk of higher disease severity and mortality. Broad geographic variability and spatiotemporal spread variation of the COVID-19 pandemic in Libya was observed, indicating a significant increase of COVID-19 spread starting in the middle of July 2020, particularly in the western and southern regions, although it was consistently reported in the central and eastern regions as well. Assessing the spatiotemporal dynamics of COVID-19 in the early stages of the epidemic is particularly important in understanding the pandemic spread. Such assessments are essential for designing effective prevention and control programs aimed at reducing the impact of the COVID- 19 pandemic, particularly in countries with limited resources.

show abstract

Spatial temporal distribution of COVID-19 risk during the early phase of the pandemic in Malawi

Cited by 11 publications

References 30 publications

Spatial Dynamics and Multiscale Regression Modelling of Population Level Indicators for COVID-19 Spread in Malaysia

Spatial Dynamics and Multiscale Regression Modelling of Population Level Indicators for COVID-19 Spread in Malaysia

Dynamics of SARS-CoV-2 exposure in Malawian blood donors: a retrospective seroprevalence analysis between January 2020 and February 2021

The Epidemiological and Spatiotemporal Characteristics of the 2019 Novel Coronavirus Disease (COVID-19) in Libya

Contact Info

Product

Resources

About